Hasso-Plattner-Institut
HPI Digital Health Center
 

Digital Health Center

2021

  • Controversial Trials First: Identifying Disagreement Between Clinical Guidelines and New Evidence. Borchert, Florian; Meister, Laura; Langer, Thomas; Follmann, Markus; Arnrich, Bert; Schapranow, Matthieu-P. (2021). (Vol. 2021) 236–245.
     
  • Data Augmentation of Kinematic Time-Series From Rehabilitation Exercises Using GANs. Albert, Justin; Glöckner, Pawel; Pfitzner, Bjarne; Arnrich, Bert (2021). 1–6.
     
  • Scientific sexism: the gender bias in the scientific production of the Universidade de São Paulo. Oliveira-Ciabati, Livia; Santos, Luciane Loures; Hsiou, Annie Schmaltz; Sasso, Ariane Morassi; Castro, Margaret; Souza, Joao Paulo in Revista de Saúde Pública (2021). 55 46.
     
  • Standardizing Clinical Predictive Modeling – Standardizing Development, Validation, and Interpretation of Clinical Prediction Models Freitas da Cruz, Harry in Doctoral Dissertation (2021). University of Potsdam.
     
  • Differentially Private Federated Learningfor Anomaly Detection in EHealth Networks. Cholakoska, Ana; Pfitzner, Bjarne; Gjoreski, Hristijan; Rakovic, Valentin; Arnrich, Bert; Kalendar, Marija in UbiComp ’21 (2021). 514–518.
     
  • Role of Individual Motivations and Privacy Concerns in the Adoption of German Electronic Patient Record Apps—A Mixed-Methods Study. Henkenjohann, Richard in International Journal of Environmental Research and Public Health (2021). 18(18) 31.
     
  • TRIPOD—A Treadmill Walking Dataset with IMU, Pressure-Distribution and Photoelectric Data for Gait Analysis. Trautmann, Justin; Zhou, Lin; Brahms, Clemens Markus; Tunca, Can; Ersoy, Cem; Granacher, Urs; Arnrich, Bert in Data (2021). 6(9) 95.
     
  • Speaking Corona? Human and Machine Recognition of COVID-19 from Voice. Hecker, Pascal; Pokorny, Florian B.; Bartl-Pokorny, Katrin D.; Reichel, Uwe; Ren, Zhao; Hantke, Simone; Eyben, Florian; Schuller, Dagmar M.; Arnrich, Bert; Schuller, Björn W. (2021). 1029–1033.
     
  • Acute Kidney Injury in Patients Hospitalized With COVID-19 in New York City: Temporal Trends From March 2020 to April 2021. Dellepiane, Sergio; Vaid, Akhil; Jaladanki, Suraj K.; Coca, Steven; Fayad, Zahi A.; Charney, Alexander W.; Bottinger, Erwin P.; He, John Cijiang; Glicksberg, Benjamin S.; Chan, Lili; Nadkarni, Girish in Kidney Medicine (2021).
     
  • Factors Associated with Longitudinal Psychological and Physiological Stress in Health Care Workers During the COVID-19 Pandemic: Observational Study Using Apple Watch Data (Preprint). Hirten, Robert P; Danieletto, Matteo; Tomalin, Lewis; Choi, Katie Hyewon; Zweig, Micol; Golden, Eddye; Kaur, Sparshdeep; Helmus, Drew; Biello, Anthony; Pyzik, Renata; Calcogna, Claudia; Freeman, Robert; Sands, Bruce E; Charney, Dennis; Bottinger, Erwin P; Murrough, James W; Keefer, Laurie; Suarez-Farinas, Mayte; Nadkarni, Girish N; Fayad, Zahi A in Journal of Medical Internet Research (2021).
     
  • Choosing the Appropriate QRS Detector. Eilers, Justus; Chromik, Jonas; Arnrich, Bert (2021). (Vol. 14)
     
  • StudyMe: A New Mobile App for User-Centric N-of-1 Trials. Zenner, Alexander M.; Bottinger, Erwin; Konigorski, Stefan (2021).
     
  • Mobile app requirements for patients with rare liver diseases: A single center survey for the ERN RARE-LIVER‬‬‬. Ruther, Darius F.; Sebode, Marcial; Lohse, Ansgar W.; Wernicke, Sarah; Boetinger, Erwin; Casar, Christian; Braun, Felix; Schramm, Christoph in Clinics and Research in Hepatology and Gastroenterology (2021). 45(6) 101760.
     
  • Domain-Specific Event Abstraction. Klessascheck, Finn; Lichtenstein, Tom; Meier, Martin; Remy, Simon; Sachs, Jan Philipp; Pufahl, Luise; Miotto, Riccardo; Bottinger, Erwin; Weske, Mathias in Business Information Systems (2021). 117–126.
     
  • Mobile app requirements for patients with rare liver diseases: A single center survey for the ERN RARE-LIVER‬‬‬. Ruther, Darius F.; Sebode, Marcial; Lohse, Ansgar W.; Wernicke, Sarah; Bottinger, Erwin; Casar, Christian; Braun, Felix; Schramm, Christoph in Clinics and Research in Hepatology and Gastroenterology (2021). 45(6) 101760.
     
  • FIBER: enabling flexible retrieval of electronic health records data for clinical predictive modeling. Datta, Suparno; Sachs, Jan Philipp; Cruz, Harry Freitas; Martensen, Tom; Bode, Philipp; Sasso, Ariane Morassi; Glicksberg, Benjamin S; Bottinger, Erwin in JAMIA Open (2021). 4(3)
     
  • Unsupervised Learning to Subphenotype Heart Failure Patients from Electronic Health Records. Hackl, Melanie; Datta, Suparno; Miotto, Riccardo; Bottinger, Erwin in Artificial Intelligence in Medicine (2021). 219–228.
     
  • Monitoring of Sitting Postures With Sensor Networks in Controlled and Free-living Environments: Systematic Review. Kappattanavar, Arpita Mallikarjuna; Steckhan, Nico; Sachs, Jan Philipp; da Cruz, Harry Freitas; Bottinger, Erwin; Arnrich, Bert in JMIR Biomedical Engineering (2021). 6(1) e21105.
     
  • Devicely: A Python package for reading, timeshifting and writing sensor data. Sasso, Ariane; Morgenstern, Jost; Musmann, Felix; Arnrich, Bert in Journal of Open Source Software (2021). 6(66) 3679.
     
  • Schneller Impfen dank Digitalisierung?. Schapranow, Matthieu-P. in Tagesspiegel Background (2021).
     
  • Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19. Vaid, Akhil; Chan, Lili; Chaudhary, Kumardeep; Jaladanki, Suraj; Paranjpe, Ishan; Russak, Adam; Kia, Arash; Timsina, Prem; Levin, Matthew; He, John; Bottinger, Erwin; Charney, Alexander; Fayad, Zahi; Coca, Steven; Glicksberg, Benjamin; Nadkarni, Girish in Clinical Journal of the American Society of Nephrology (2021). CJN.17311120.
     
  • A Resilience-Building App to Support the Mental Health of Health Care Workers in the COVID-19 Era: Design Process, Distribution, and Evaluation. Golden, Eddye A; Zweig, Micol; Danieletto, Matteo; Landell, Kyle; Nadkarni, Girish; Bottinger, Erwin; Katz, Lindsay; Somarriba, Ricardo; Sharma, Vansh; Katz, Craig L; Marin, Deborah B; DePierro, Jonathan; Charney, Dennis S in JMIR Formative Research (2021). 5(5) e26590.
     
  • Toward a fine-scale population health monitoring system. Belbin, Gillian M.; Cullina, Sinead; Wenric, Stephane; Soper, Emily R.; Glicksberg, Benjamin S.; Torre, Denis; Moscati, Arden; Wojcik, Genevieve L.; Shemirani, Ruhollah; Beckmann, Noam D.; Cohain, Ariella; Sorokin, Elena P.; Park, Danny S.; Ambite, Jose-Luis; Ellis, Steve; Auton, Adam; Bottinger, Erwin P.; Cho, Judy H.; Loos, Ruth J.F.; Abul-Husn, Noura S.; Zaitlen, Noah A.; Gignoux, Christopher R.; Kenny, Eimear E. in Cell (2021). 184(8) 2068–2083.e11.
     
  • Optimal Sensor Placement for Human Activity Recognition with a Minimal Smartphone–IMU Setup. Rahn, Vincent Xeno; Zhou, Lin; Klieme, Eric; Arnrich, Bert (2021). (Vol. 10) 37–48.
     
  • Kidney disease genetic risk variants alter lysosomal beta-mannosidase (MANBA) expression and disease severity. Gu, Xiangchen; Yang, Hongliu; Sheng, Xin; Ko, Yi-An; Qiu, Chengxiang; Park, Jihwan; Huang, Shizheng; Kember, Rachel; Judy, Renae L.; Park, Joseph; Damrauer, Scott M.; Nadkarni, Girish; Loos, Ruth J. F.; My, Vy Thi Ha; Chaudhary, Kumardeep; Bottinger, Erwin P.; Paranjpe, Ishan; Saha, Aparna; Brown, Christopher; Akilesh, Shreeram; Hung, Adriana M.; Palmer, Matthew; Baras, Aris; Overton, John D.; Reid, Jeffrey; Ritchie, Marylyn; Rader, Daniel J.; Susztak, Katalin in Science Translational Medicine (2021). 13(576) eaaz1458.
     
  • Knowledge bases and software support for variant interpretation in precision oncology. Borchert, Florian; Mock, Andreas; Tomczak, Aurelie; Hügel, Jonas; Alkarkoukly, Samer; Knurr, Alexander; Volckmar, Anna-Lena; Stenzinger, Albrecht; Schirmacher, Peter; Debus, Jürgen; Jäger, Dirk; Longerich, Thomas; Fröhling, Stefan; Eils, Roland; Bougatf, Nina; Sax, Ulrich; Schapranow, Matthieu-P in Briefings in Bioinformatics (2021). 22(6)
     
  • GAIA-X: A Pitch Towards Europe Affairs, Federal Ministry of Economic; Energy (BMWi); others (2021).
     
  • Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study. Hirten, Robert P; Danieletto, Matteo; Tomalin, Lewis; Choi, Katie Hyewon; Zweig, Micol; Golden, Eddye; Kaur, Sparshdeep; Helmus, Drew; Biello, Anthony; Pyzik, Renata; Charney, Alexander; Miotto, Riccardo; Glicksberg, Benjamin S; Levin, Matthew; Nabeel, Ismail; Aberg, Judith; Reich, David; Charney, Dennis; Bottinger, Erwin P; Keefer, Laurie; Suarez-Farinas, Mayte; Nadkarni, Girish N; Fayad, Zahi A in Journal of Medical Internet Research (2021). 23(2) e26107.
     
  • Certainty in QRS detection with artificial neural networks. Chromik, Jonas; Pirl, Lukas; Beilharz, Jossekin; Arnrich, Bert; Polze, Andreas in Biomedical Signal Processing and Control (2021). 68 102628.
     
  • Monitoring of Sitting Postures With Sensor Networks in Controlled and Free-living Environments: Systematic Review. Kappattanavar, Arpita Mallikarjuna; Steckhan, Nico; Sachs, Jan Philipp; Freitas da Cruz, Harry; Boettinger, Erwin; Arnrich, Bert in JMIR Biomed Eng (2021). 6(1) e21105.
     
  • Association of SARS-CoV-2 viral load at admission with in-hospital acute kidney injury: A retrospective cohort study. Paranjpe, Ishan; Chaudhary, Kumardeep; Johnson, Kipp W.; Jaladanki, Suraj K.; Zhao, Shan; Freitas, Jessica K. De; Pujdas, Elisabet; Chaudhry, Fayzan; Bottinger, Erwin P.; Levin, Matthew A.; Fayad, Zahi A.; Charney, Alexander W.; Houldsworth, Jane; Cordon-Cardo, Carlos; Glicksberg, Benjamin S.; Nadkarni, Girish N. in PLOS ONE, (A. L. Conroy, ed.) (2021). 16(2) e0247366.
     
  • Biomedical and Clinical Research Data Management. Ganzinger, Matthias; Glaab, Enrico; Kerssemakers, Jules; Nahnsen, Sven; Sax, Ulrich; Schaadt, Nadine Sarah; Schapranow, Matthieu-P.; Tiede, Thorsten in Systems Medicine, O. Wolkenhauer (ed.) (2021). 532–543.
     
  • Federated Learning of Electronic Health Records to Improve Mortality Prediction in Hospitalized Patients With COVID-19: Machine Learning Approach. Vaid, Akhil; Jaladanki, Suraj K; Xu, Jie; Teng, Shelly; Kumar, Arvind; Lee, Samuel; Somani, Sulaiman; Paranjpe, Ishan; Freitas, Jessica K De; Wanyan, Tingyi; Johnson, Kipp W; Bicak, Mesude; Klang, Eyal; Kwon, Young Joon; Costa, Anthony; Zhao, Shan; Miotto, Riccardo; Charney, Alexander W; Böttinger, Erwin; Fayad, Zahi A; Nadkarni, Girish N; Wang, Fei; Glicksberg, Benjamin S in JMIR Medical Informatics (2021). 9(1) e24207.
     
  • Temporal Trends in COVID-19 associated AKI from March to December 2020 in New York City. Dellepiane, Sergio; Vaid, Akhil; Jaladanki, Suraj K; Paranjpe, Ishan; Coca, Steven; Fayad, Zahi A; Charney, Alexander W; Bottinger, Erwin P; He, John Cijiang; Glicksberg, Benjamin S; Chan, Lili; Nadkarni, Girish (2021).
     
  • Causal inference in developmental medicine and neurology. Konigorski, Stefan in Developmental Medicine & Child Neurology (2021).
     
  • Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19. Vaid, Akhil; Chan, Lili; Chaudhary, Kumardeep; Jaladanki, Suraj K.; Paranjpe, Ishan; Russak, Adam; Kia, Arash; Timsina, Prem; Levin, Matthew A.; He, John Cijiang; Boettinger, Erwin P.; Charney, Alexander W.; Fayad, Zahi A.; Coca, Steven G.; Glicksberg, Benjamin S.; Nadkarni, Girish N. in Clinical Journal of the American Society of Nephrology (2021). 16(8) 1158–1168.
     

2020

  • Economic impact of clinical decision support interventions based on electronic health records. Lewkowicz, Daniel; Wohlbrandt, Attila; Boettinger, Erwin in BMC Health Services Research (2020). 20(1)
     
  • HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population. Morassi Sasso, Ariane; Datta, Suparno; Jeitler, Michael; Steckhan, Nico; Kessler, Christian S.; Michalsen, Andreas; Arnrich, Bert; Böttinger, Erwin M. Michalowski, R. Moskovitch (eds.) (2020). (Vol. 12299)
     
  • Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization for COVID-19. Somani, Sulaiman S.; Richter, and Felix; Fuster, Valentin; Freitas, Jessica K. De; Naik, Nidhi; Sigel, Keith; Bottinger, Erwin P; Levin, Matthew A.; Fayad, Zahi; Just, Allan C.; Charney, Alexander W.; Zhao, Shan; Glicksberg, Benjamin S.; Lala, Anuradha; Nadkarni, Girish N. in Journal of General Internal Medicine (2020). 35(10) 2838–2844.
     
  • Coronavirus 2019 and People Living With Human Immunodeficiency Virus: Outcomes for Hospitalized Patients in New York City. Sigel, Keith; Swartz, Talia; Golden, Eddye; Paranjpe, Ishan; Somani, Sulaiman; Richter, Felix; Freitas, Jessica K De; Miotto, Riccardo; Zhao, Shan; Polak, Paz; Mutetwa, Tinaye; Factor, Stephanie; Mehandru, Saurabh; Mullen, Michael; Cossarini, Francesca; Bottinger, Erwin; Fayad, Zahi; Merad, Miriam; Gnjatic, Sacha; Aberg, Judith; Charney, Alexander; Nadkarni, Girish; Glicksberg, Benjamin S in Clinical Infectious Diseases (2020).
     
  • Literature Review on Transfer Learning for Human Activity Recognition Using Mobile and Wearable Devices with Environmental Technology. Hernandez, Netzahualcoyotl; Lundström, Jens; Favela, Jesus; McChesney, Ian; Arnrich, Bert in SN Computer Science (2020). 1(2) 66.
     
  • Towards the automatic detection of social biomarkers in autism spectrum disorder: introducing the simulated interaction task (SIT). Drimalla, Hanna; Scheffer, Tobias; Landwehr, Niels; Baskow, Irina; Roepke, Stefan; Behnia, Behnoush; Dziobek, Isabel in npj digital medicine (2020). 3(25)
     
  • Self-prediction of seizures in drug resistance epilepsy using digital phenotyping: a concept study. Moontaha, Sidratul; Steckhan, Nico; Kappattanavar, Arpita; Surges, Rainer; Arnrich, Bert (2020). (Vol. 14)
     
  • Phe2vec: Automated Disease Phenotyping based on Unsupervised Embeddings from Electronic Health Records. Freitas, Jessica K. De; Johnson, Kipp W.; Golden, Eddye; Nadkarni, Girish N.; Dudley, Joel T.; Bottinger, Erwin P.; Glicksberg, Benjamin S.; Miotto, Riccardo (2020).
     
  • Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19. Chan, Lili; Jaladanki, Suraj K.; Somani, Sulaiman; Paranjpe, Ishan; Kumar, Arvind; Zhao, Shan; Kaufman, Lewis; Leisman, Staci; Sharma, Shuchita; He, John Cijiang; Murphy, Barbara; Fayad, Zahi A.; Levin, Matthew A.; Bottinger, Erwin P.; Charney, Alexander W.; Glicksberg, Benjamin S.; Coca, Steven G.; Nadkarni, Girish N. in Clinical Journal of the American Society of Nephrology (2020). 16(3) 452–455.
     
  • Schöne neue Ärzte-Welt: Kümmern sich kluge Computer bald um unsere Gesundheitsprobleme?. Schapranow, Matthieu-P. in F.A.Z. Sonderbeliage Gesundheit (2020). (48) B2.
     
  • Good news: How data science helps us to better understand the Coronavirus pandemic. Schapranow, Matthieu-P. in Portal Wissen: The research magazine of the University of Potsdam (2020). 2(9) 14–19.
     
  • ALPS: A Web Platform for Analysing Multimodal Sensor Data in the Context of Digital Health. Musmann, F.; Sasso, A.; Arnrich, B. (2020). 1–12.
     
  • Physiological Data from a Wearable Device Identifies SARS-CoV-2 Infection and Symptoms and Predicts COVID-19 Diagnosis: Observational Study (Preprint). Hirten, Robert P; Danieletto, Matteo; Tomalin, Lewis; Choi, Katie Hyewon; Zweig, Micol; Golden, Eddye; Kaur, Sparshdeep; Helmus, Drew; Biello, Anthony; Pyzik, Renata; Charney, Alexander; Miotto, Riccardo; Glicksberg, Benjamin S; Levin, Matthew; Nabeel, Ismail; Aberg, Judith; Reich, David; Charney, Dennis; Bottinger, Erwin P; Keefer, Laurie; Suarez-Farinas, Mayte; Nadkarni, Girish N; Fayad, Zahi A in Journal of Medical Internet Research (2020).
     
  • IMU-Based Movement Trajectory Heatmaps for Human Activity Recognition. Konak, Orhan; Wegner, Pit; Arnrich, Bert in Sensors (Switzerland) (2020). 20(24) 1–15.
     
  • Eatomics: Shiny exploration of quantitative proteomics data. Kraus, Milena; Mathew Stephen, Mariet; Schapranow, Matthieu-P in Journal of Proteome Research, (S. Weintraub, ed.) (2020).
     
  • Spotlight on Women in Tech: Fostering an Inclusive Workforce when Exploring and Exploiting Digital Innovation Potentials. Schmitt, Franziska; Sundermeier, Janina; Bohn, Nicolai; Morassi Sasso, Ariane (2020). (Vol. 6)
     
  • StudyU: a platform for designing and conducting innovative digital N-of-1 trials Konigorski, Stefan; Wernicke, Sarah; Slosarek, Tamara; Zenner, Alexander M.; Strelow, Nils; Ruether, Ferenc D.; Henschel, Florian; Manaswini, Manisha; Pottbäcker, Fabian; Edelman, Jonathan A.; Owoyele, Babajide; Danieletto, Matteo; Golden, Eddye; Zweig, Micol; Nadkarni, Girish; Böttinger, Erwin (2020).
     
  • IMU-Based Movement Trajectory Heatmaps for Human Activity Recognition. Konak, Orhan; Wegner, Pit; Arnrich, Bert in Sensors (2020). 20(24) 7179.
     
  • Prototypical System to Detect Anxiety Manifestations by Acoustic Patterns in Patients with Dementia. Hernandez, Netzahualcoyotl; Garcia-Constantino, Matias; Beltran, Jessica; Hecker, Pascal; Favela, Jesus; Cleland, Ian; Lopez, Hussein; Arnrich, Bert; McChesney, Ian in EAI Endorsed Transactions on Pervasive Health and Technology (2020). 5(19)
     
  • Will You Be My Quarantine: A Computer Vision and Inertial Sensor Based Home Exercise System. Albert, Justin; Zhou, Lin; Gloeckner, Pawel; Trautmann, Justin; Ihde, Lisa; Eilers, Justus; Kamal, Mohammed; Arnrich, Bert (2020). (Vol. 14)
     
  • AKI in Hospitalized Patients with COVID-19. Chan, Lili; Chaudhary, Kumardeep; Saha, Aparna; Chauhan, Kinsuk; Vaid, Akhil; Zhao, Shan; Paranjpe, Ishan; Somani, Sulaiman; Richter, Felix; Miotto, Riccardo; Lala, Anuradha; Kia, Arash; Timsina, Prem; Li, Li; Freeman, Robert; Chen, Rong; Narula, Jagat; Just, Allan C.; Horowitz, Carol; Fayad, Zahi; Cordon-Cardo, Carlos; Schadt, Eric; Levin, Matthew A.; Reich, David L.; Fuster, Valentin; Murphy, Barbara; He, John C.; Charney, Alexander W.; Böttinger, Erwin P.; Glicksberg, Benjamin S.; Coca, Steven G.; Nadkarni, Girish N. in Journal of the American Society of Nephrology (2020). 32(1) 151–160.
     
  • The effect of LRRK2 loss-of-function variants in humans. Whiffin, Nicola; Armean, and Irina M.; Kleinman, Aaron; Marshall, Jamie L.; Minikel, Eric V.; Goodrich, Julia K.; Quaife, Nicholas M.; Cole, Joanne B.; Wang, Qingbo; Karczewski, Konrad J.; Cummings, Beryl B.; Francioli, Laurent; Laricchia, Kristen; Guan, Anna; Alipanahi, Babak; Morrison, Peter; Baptista, Marco A. S.; Merchant, Kalpana M.; Ware, James S.; Havulinna, Aki S.; Iliadou, Bozenna; Lee, Jung-Jin; Nadkarni, Girish N.; Whiteman, Cole; Daly, Mark; Esko, T~onu; Hultman, Christina; Loos, Ruth J. F.; Milani, Lili; Palotie, Aarno; Pato, Carlos; Pato, Michele; Saleheen, Danish; Sullivan, Patrick F.; Alföldi, Jessica; Cannon, Paul; MacArthur, Daniel G.; and in Nature Medicine (2020). 26(6) 869–877.
     
  • Federated Learning in a Medical Context: A Systematic Literature Review. Pfitzner, Bjarne; Steckhan, Nico; Arnrich, Bert in ACM Transactions on Internet Technology (TOIT) Special Issue on Security and Privacy of Medical Data for Smart Healthcare (2020).
     
  • Tangle Ledger for Decentralized Learning. Schmid, R.; Pfitzner, B.; Beilharz, J.; Arnrich, B.; Polze, A. (2020). 852–859.
     
  • Validation of an IMU Gait Analysis Algorithm for Gait Monitoring in Daily Life Situations. Zhou, Lin; Tunca, Can; Fischer, Eric; Brahms, Clemens Markus; Ersoy, Cem; Granacher, Urs; Arnrich, Bert (2020).
     
  • How We Found Our IMU: Guidelines to IMU Selection and a Comparison of Seven IMUs for Pervasive Healthcare Applications. Zhou, Lin; Fischer, Eric; Tunca, Can; Brahms, Clemens Markus; Ersoy, Cem; Granacher, Urs; Arnrich, Bert in Sensors (2020).
     
  • Proteomic analysis reveals upregulation of ACE2, the putative SARS-CoV-2 receptor in pressure- but not volume-overloaded human hearts. Stegbauer, Johannes Stegbauer; Kraus, Milena; Nordmeyer, Sarah; Kirchner, Marieluise; Ziehm, Matthias Ziehm; Dommisch, Henrik; Kelle, Sebastian; Kelm, Marcus; Baczko, Istvan; Landmesser, Ulf; Tschope, Carsten; Knosalla, Christoph; Falcke, Martin; Schapranow, Matthieu-P.; Regitz-Zagrosek, Vera; Mertins, Philipp; Kühne, Titus in Hypertension (2020).
     
  • HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population. Sasso, Ariane Morassi; Datta, Suparno; Jeitler, Michael; Steckhan, Nico; Kessler, Christian S; Michalsen, Andreas; Arnrich, Bert; Boettinger, Erwin (2020). 325–335.
     
  • It is time to reality check the promises of machine learning-powered precision medicine. Wilkinson, Jack; Arnold, Kellyn F; Murray, Eleanor J; van Smeden, Maarten; Carr, Kareem; Sippy, Rachel; de Kamps, Marc; Beam, Andrew; Konigorski, Stefan; Lippert, Christoph; Gilthorpe, Mark S; Tennant, Peter WG in The Lancet Digital Health (2020).
     
  • Using Interpretability Approaches to Update Black-Box Clinical Prediction Models: an External Validation Study in Nephrology. da Cruz, Harry Freitas; Pfahringer, Boris; Martensen, Tom; Schneider, Frederic; Meyer, Alexander; Bottinger, Erwin; Schapranow, Matthieu-P. in Artificial Intelligence in Medicine (2020). 101982.
     
  • Directed Acyclic Graphs and causal thinking in clinical risk prediction modeling. Piccininni, Marco; Konigorski, Stefan; Rohmann, Jessica L; Kurth, Tobias in BMC Medical Research Methodology (2020). 20 179.
     
  • Latente Tuberkulose bei medizinischem Personal in Deutschland nach Auslandseinsatz. Meier, I; Schablon, A; Nienhaus, A; Konigorski, S in Pneumologie (2020). 74 1–7.
     
  • Fast kernel-based rare-variant association tests integrating variant annotations from deep learning. Konigorski, S; Monti, R; Rautenstrauch, P; Lippert, C (2020). (Vol. 44) 495.
     
  • The SARS-CoV-2 effective reproduction rate has a high correlation with a contact index derived from large-scale individual location data using GPS-enabled mobile phones in Germany Rüdiger, S; Konigorski, S; Edelman, J; Zernick, D; Lippert, C; Thieme, A (2020).
     
  • GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines. Borchert, Florian; Lohr, Christina; Modersohn, Luise; Langer, Thomas; Follmann, Markus; Sachs, Jan Philipp; Hahn, Udo; Schapranow, Matthieu-P. (2020). 38–48.
     
  • Good News: Wie Data Science dabei hilft, die Corona-Pandemie besser zu verstehen. Schapranow, Matthieu-P. in Portal Wissen: Das Forschungsmagazin der Universität Potsdam (2020). 9(2) 14–19.
     
  • Data Science für Digitale Medizin. Fehr, J; Konigorski, S; Lippert, C D. Matusiewicz, M. Henningsen, J. Ehlers (eds.) (2020). (Vol. Digitale Medizin – Kompendium für Studium und Praxis)
     
  • "Herr Doktor, verstehen Sie mich?“: Wie lernende Systeme helfen medizinische Fachsprache zu verstehen und welche Rolle klinische Leitlinien dabei spielen. Borchert, Florian; Lohr, Christina; Modersohn, Luise; Hahn, Udo; Langer, Thomas; Wenzel, Gregor; Follmann, Markus; Schapranow, Matthieu-P. in gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland (2020). 13 19–22.
     
  • #nCoVStats: Wie Data Science hilft die Coronavirus-Pandemie zu verstehen. Schapranow, Matthieu-P. in gesundhyte.de: Das Magazin für Digitale Gesundheit in Deutschland (2020). 13 34–37.
     
  • Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation. Vaid, Akhil; Somani, Sulaiman; Russak, Adam J; Freitas, Jessica K De; Chaudhry, Fayzan F; Paranjpe, Ishan; Johnson, Kipp W; Lee, Samuel J; Miotto, Riccardo; Richter, Felix; Zhao, Shan; Beckmann, Noam D; Naik, Nidhi; Kia, Arash; Timsina, Prem; Lala, Anuradha; Paranjpe, Manish; Golden, Eddye; Danieletto, Matteo; Singh, Manbir; Meyer, Dara; OtextquotesingleReilly, Paul F; Huckins, Laura; Kovatch, Patricia; Finkelstein, Joseph; Freeman, Robert M.; Argulian, Edgar; Kasarskis, Andrew; Percha, Bethany; Aberg, Judith A; Bagiella, Emilia; Horowitz, Carol R; Murphy, Barbara; Nestler, Eric J; Schadt, Eric E; Cho, Judy H; Cordon-Cardo, Carlos; Fuster, Valentin; Charney, Dennis S; Reich, David L; Bottinger, Erwin P; Levin, Matthew A; Narula, Jagat; Fayad, Zahi A; Just, Allan C; Charney, Alexander W; Nadkarni, Girish N; Glicksberg, Benjamin S in Journal of Medical Internet Research (2020). 22(11) e24018.
     
  • Evaluation of the Pose Tracking Performance of the Azure Kinect and Kinect v2 for Gait Analysis in Comparison with a Gold Standard: A Pilot Study. Albert, Justin; Owolabi, Victor; Gebel, Arnd; Brahms, Markus Clemens; Granacher, Urs; Arnrich, Bert in MDPI Sensors (2020). 20(18)
     
  • Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19. Chan, Lili; Jaladanki, Suraj K.; Somani, Sulaiman; Paranjpe, Ishan; Kumar, Arvind; Zhao, Shan; Kaufman, Lewis; Leisman, Staci; Sharma, Shuchita; He, John Cijiang; Murphy, Barbara; Fayad, Zahi A.; Levin, Matthew A.; Bottinger, Erwin P.; Charney, Alexander W.; Glicksberg, Benjamin S.; Coca, Steven G.; Nadkarni, Girish N. in Clinical Journal of the American Society of Nephrology (2020). CJN.12360720.
     
  • Genetic Studies of Leptin Concentrations Implicate Leptin in the Regulation of Early Adiposity. Yaghootkar, Hanieh; Zhang, Yiying; Spracklen, Cassandra N; Karaderi, Tugce; Huang, Lam Opal; Bradfield, Jonathan; Schurmann, Claudia; Fine, Rebecca S; Preuss, Michael H; Kutalik, Zoltan; Wittemans, Laura Bl; Lu, Yingchang; Metz, Sophia; Willems, Sara M; Li-Gao, Ruifang; Grarup, Niels; Wang, Shuai; Molnos, Sophie; Sandoval-Zárate, América A; Nalls, Mike A; Lange, Leslie A; Haesser, Jeffrey; Guo, Xiuqing; Lyytikäinen, Leo-Pekka; Feitosa, Mary F; Sitlani, Colleen M; Venturini, Cristina; Mahajan, Anubha; Kacprowski, Tim; Wang, Carol A; Chasman, Daniel I; Amin, Najaf; Broer, Linda; Robertson, Neil; Young, Kristin L; Allison, Matthew; Auer, Paul L; Blüher, Matthias; Borja, Judith B; Bork-Jensen, Jette; Carrasquilla, Germán D; Christofidou, Paraskevi; Demirkan, Ayse; Doege, Claudia A; Garcia, Melissa E; Graff, Mariaelisa; Guo, Kaiying; Hakonarson, Hakon; Hong, Jaeyoung; Ida Chen, Yii-Der; Jackson, Rebecca; Jakupović, Hermina; Jousilahti, Pekka; Justice, Anne E; Kähönen, Mika; Kizer, Jorge R; Kriebel, Jennifer; LeDuc, Charles A; Li, Jin; Lind, Lars; Luan, Jian’an; Mackey, David; Mangino, Massimo; Männistö, Satu; Martin Carli, Jayne F; Medina-Gomez, Carolina; Mook-Kanamori, Dennis O; Morris, Andrew P; de Mutsert, Renée; Nauck, Matthias; Nedeljkovic, Ivana; Pennell, Craig E; Pradhan, Arund D; Psaty, Bruce M; Raitakari, Olli T; Scott, Robert A; Skaaby, Tea; Strauch, Konstantin; Taylor, Kent D; Teumer, Alexander; Uitterlinden, Andre G; Wu, Ying; Yao, Jie; Walker, Mark; North, Kari E; Kovacs, Peter; Ikram, M Arfan; van Duijn, Cornelia M; Ridker, Paul M; Lye, Stephen; Homuth, Georg; Ingelsson, Erik; Spector, Tim D; McKnight, Barbara; Province, Michael A; Lehtimäki, Terho; Adair, Linda S; Rotter, Jerome I; Reiner, Alexander P; Wilson, James G; Harris, Tamara B; Ripatti, Samuli; Grallert, Harald; Meigs, James B; Salomaa, Veikko; Hansen, Torben; Willems van Dijk, Ko; Wareham, Nicholas J; Grant, Struan Fa; Langenberg, Claudia; Frayling, Timothy M; Lindgren, Cecilia M; Mohlke, Karen L; Leibel, Rudolph L; Loos, Ruth Jf; Kilpeläinen, Tuomas O in Diabetes (2020).
     
  • Event Log Generation in a Health System: A Case Study. Remy, Simon; Pufahl, Luise; Sachs, Jan Philipp; Böttinger, Erwin; Weske, Mathias in Lecture Notes in Computer Science (2020). 505–522.
     
  • Exome sequencing and characterization of 49,960 individuals in the UK Biobank. Van Hout, Cristopher V; Tachmazidou, Ioanna; Backman, Joshua D; Hoffman, Joshua D; Liu, Daren; Pandey, Ashutosh K; Gonzaga-Jauregui, Claudia; Khalid, Shareef; Ye, Bin; Banerjee, Nilanjana; Li, Alexander H; O’Dushlaine, Colm; Marcketta, Anthony; Staples, Jeffrey; Schurmann, Claudia; Hawes, Alicia; Maxwell, Evan; Barnard, Leland; Lopez, Alexander; Penn, John; Habegger, Lukas; Blumenfeld, Andrew L; Bai, Xiaodong; O’Keeffe, Sean; Yadav, Ashish; Praveen, Kavita; Jones, Marcus; Salerno, William J; Chung, Wendy K; Surakka, Ida; Willer, Cristen J; Hveem, Kristian; Leader, Joseph B; Carey, David J; Ledbetter, David H; Cardon, Lon; Yancopoulos, George D; Economides, Aris; Coppola, Giovanni; Shuldiner, Alan R; Balasubramanian, Suganthi; Cantor, Michael; Nelson, Matthew R; Whittaker, John; Reid, Jeffrey G; Marchini, Jonathan; Overton, John D; Scott, Robert A; Abecasis, Gonçalo R; Yerges-Armstrong, Laura; Baras, Aris in Nature (2020).
     
  • Constrained expectation maximisation algorithm for estimating ARMA models in state space representation. Galka, Andreas; Moontaha, Sidratul; SIniatchkin, Siniatchkin in EURASIP Journal on Advances in Signal Processing 2020.1 (2020). 1–37.
     
  • Powerful rare variant association testing in a copula-based joint analysis of multiple traits. Konigorski, Stefan; Yilmaz, Yildiz E.; Janke, Jürgen; Bergmann, Manuela M.; Boeing, Heiner; Pischon, Tobias in Genetic Epidemiology (2020). 44(1) 26–40.
     
  • Hand in Hand: Wie KI und Ärzte in der Onkologie zusammenarbeiten. Schapranow, Matthieu-P. in Konkrete Anwendungsfälle von KI & Big-Data in der Industrie (2020). 69–74.
     
  • Using CEF Digital Service Infrastructures in the Smart4Health Project for the Exchange of Electronic Health Records. Slosarek, Tamara; Wohlbrandt, Attila; Böttinger, Erwin in arXiv preprint arXiv:2001.01477 (2020).
     
  • Clinical Characteristics of Hospitalized Covid-19 Patients in New York City. Paranjpe, Ishan; Russak, Adam; Freitas, Jessica K De; Lala, Anuradha; Miotto, Riccardo; Vaid, Akhil; Johnson, Kipp W; Danieletto, Matteo; Golden, Eddye; Meyer, Dara; Singh, Manbir; Somani, Sulaiman; Manna, Sayan; Nangia, Udit; Kapoor, Arjun; OtextquotesingleHagan, Ross; OtextquotesingleReilly, Paul F; Huckins, Laura M; Glowe, Patricia; Kia, Arash; Timsina, Prem; Freeman, Robert M; Levin, Matthew A; Jhang, Jeffrey; Firpo, Adolfo; Kovatch, Patricia; Finkelstein, Joseph; Aberg, Judith A; Bagiella, Emilia; Horowitz, Carol R; Murphy, Barbara; Fayad, Zahi A; Narula, Jagat; Nestler, Eric J; Fuster, Valentin; Cordon-Cardo, Carlos; Charney, Dennis S; Reich, David L; Just, Allan C; Bottinger, Erwin P; Charney, Alexander W; Glicksberg, Benjamin S; Nadkarni, Girish in medRxiv (2020). (I) Version 1 (April 23, 2020 – 03:18).
     
  • Association of APOL1 Risk Genotype and Air Pollution for Kidney Disease. Paranjpe, Ishan; Chaudhary, Kumardeep; Paranjpe, Manish; O’Hagan, Ross; Manna, Sayan; Jaladanki, Suraj; Kapoor, Arjun; Horowitz, Carol; DeFelice, Nicholas; Cooper, Richard; Glicksberg, Benjamin; Bottinger, Erwin P.; Just, Allan C.; Nadkarni, Girish N. in Clinical Journal of the American Society of Nephrology (2020). 15(3) 401–403.
     
  • The Influence of Reward on Facial Mimicry: No Evidence for a Significant Effect of Oxytocin. Trilla, Irene; Drimalla, Hanna; Bajbouj, Malek; Dziobek, Isabel in Frontiers in Behavioural Neuroscience (2020).
     
  • AKI in Hospitalized Patients with COVID-19. Chan, Lili; Chaudhary, Kumardeep; Saha, Aparna; Chauhan, Kinsuk; Vaid, Akhil; Zhao, Shan; Paranjpe, Ishan; Somani, Sulaiman; Richter, Felix; Miotto, Riccardo; Lala, Anuradha; Kia, Arash; Timsina, Prem; Li, Li; Freeman, Robert; Chen, Rong; Narula, Jagat; Just, Allan C.; Horowitz, Carol; Fayad, Zahi; Cordon-Cardo, Carlos; Schadt, Eric; Levin, Matthew A.; Reich, David L.; Fuster, Valentin; Murphy, Barbara; He, John C.; Charney, Alexander W.; Böttinger, Erwin P.; Glicksberg, Benjamin S.; Coca, Steven G.; Nadkarni, Girish N.; Li, Li in Journal of the American Society of Nephrology (2020). ASN.2020050615.
     
  • Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury. Chaudhary, Kumardeep; Vaid, Akhil; Duffy, Áine; Paranjpe, Ishan; Jaladanki, Suraj; Paranjpe, Manish; Johnson, Kipp; Gokhale, Avantee; Pattharanitima, Pattharawin; Chauhan, Kinsuk; O’Hagan, Ross; Vleck, Tielman Van; Coca, Steven G.; Cooper, Richard; Glicksberg, Benjamin; Bottinger, Erwin P.; Chan, Lili; Nadkarni, Girish N. in Clinical Journal of the American Society of Nephrology (2020). CJN.09330819.
     
  • Position Matters: Sensor Placement for SittingPosture Classification. Kappattanavar, A. M.; da Cruz, H. F.; Arnrich, B.; Böttinger, E. (2020).
     

2019

  • External Validation of a Black-Box Clinical Predictive Model in Nephrology: Can Interpretability Methods Help Illuminate Performance Differences?. Freitas da Cruz, Harry; Pfahringer, Boris; Schneider, Frederic; Meyer, Alexander; Schapranow, Matthieu-P. (2019). 191–201.
     
  • Association of dietary intake of milk and dairy products with blood concentrations of insulin-like growth factor 1 (IGF-1) in Bavarian adults. Romo Ventura, E; Konigorski, S; Rohrmann, S; Schneider, H; Stalla, GK; Pischon, T; Linseisen, J; Nimptsch, K in European Journal of Nutrition (2019). 59 1413–1420.
     
  • Bewertung von Therapieeffekten bei Epilepsie: Eine vergleichende Analyse zwischen Cox-Stuart-Berechnung und Zustandsraum-Modellierung Scharlach, Sascha; Moontaha, Sirdatul; von Spiczak, Sarah; Stephani, Ulrich; Siniatchkin, Michael; May, Theodor; Galka, Andreas; Meurer, Thomas (2019).
     
  • Poisoning Attacks with Generative Adversarial Nets Muñoz-González, Luis; Pfitzner, Bjarne; Russo, Matteo; Carnerero-Cano, Javier; Lupu, Emil C (2019).
     
  • Stress detection in daily life scenarios using smart phones and wearable sensors: A survey. Yekta Said, Can; Arnrich, Bert; Ersoy, Cem in Journal of Biomedical Informatics (2019). 92 103139.
     
  • MORPHER – A Platform to Support Modeling of Outcome and Risk Prediction in Health Research. Freitas da Cruz, Harry; Bergner, Benjamin; Konak, Orhan; Schneider, Frederic; Bode, Philipp; Lempert, Conrad; Schapranow, Matthieu-P. (2019).
     
  • An Exploratory Study to Detect Temporal Orientation Using Bluetooth’s sensor. Netzahualcoyotl, Hernandez; Demiray, Burcu; Arnrich, Bert; Favela, Jesus (2019). (Vol. 13) 292–297.
     
  • Digital Transformation of Complementary and Alternative Medicine (Accepted Presubmission). Steckhan, Nico; Arnrich, Bert in Complementary Medicine Research (2019).
     
  • A multi-site study on walkability, data sharing and privacy perception using mobile sensing data gathered from the mk-sense platform. Hernández, N; Arnrich, Bert; Favela, J; Ersoy, C; Demiray, Burcu; Fontecha, J in Journal of Ambient Intelligence and Humanized Computing (2019). 10 2199–2211.
     
  • Unobtrusive Measurement of Blood Pressure During Lifestyle Interventions. Morassi Sasso, Ariane; Datta, Suparno; Pfitzner, Bjarne; Zhou, Lin; Steckhan, Nico; Boettinger, Erwin; Arnrich, Bert (2019).
     
  • Integrative Network Analysis Of Microbiome-Immune Axis In Metabolic Syndrome Patients During A Fasting Intervention. Avery, Ellen G; Balogh, András; Bartolomaeus, Hendrik; Löber, Ulrike; Steckhan, Nico; Markó, Lajos; Wilck, Nicola; Hamad, Ibrahim; Šušnjar, Urša; Mähler, Anja; Hohmann, Christoph; Lesker, Till R; Strowig, Till; Dechend, Ralf; Bzdok, Danilo; Kleinewietfeld, Markus; Andreas, Michalsen; Müller, Dominik N; Forslund, Sofia K in Hypertension (2019). 74(Suppl_1)
     
  • Towards a fine-scale population health monitoring system. Belbin, Gillian M; Wenric, Stephane; Cullina, Sinead; Glicksberg, Benjamin S; Moscati, Arden; Wojcik, Genevieve L; Shemirani, Ruhollah; Beckmann, Noam D; Cohain, Ariella; Sorokin, Elena P; Park, Danny S; Ambite, Jose-Luis; Ellis, Steve; Auton, Adam; Bottinger, Erwin P.; Cho, Judy H; Loos, Ruth JF; Abul husn, Noura S; Zaitlen, Noah A; Gignoux, Christopher R; Kenny, Eimear E; and (2019).
     
  • SVD Square-root Iterated Extended Kalman Filter for Modeling of Epileptic Seizure Count Time Series with External Inputs. Moontaha, Sidratul; Galka, Andreas; Siniatchkin, Michael; Scharlach, Sascha; von Spiczak, Sarah; Stephani, Ulrich; May, Theodor; Meurer, Thomas (2019). (Vol. 41) 616–619.
     
  • From face to face: the contribution of facial mimicry to cognitive and emotional empathy. Drimalla, Hanna; Landwehr, Niels; Hess, Ursula; Dziobek, Isabel in Cognition and Emotion (2019). 33(8) 1672–1686.
     
  • Genetic analyses of diverse populations improves discovery for complex traits. Wojcik, Genevieve L; Graff, Mariaelisa; Nishimura, Katherine K; Tao, Ran; Haessler, Jeffrey; Gignoux, Christopher R; Highland, Heather M; Patel, Yesha M; Sorokin, Elena P; Avery, Christy L; Belbin, Gillian M; Bien, Stephanie A; Cheng, Iona; Cullina, Sinead; Hodonsky, Chani J; Hu, Yao; Huckins, Laura M; Jeff, Janina; Justice, Anne E; Kocarnik, Jonathan M; Lim, Unhee; Lin, Bridget M; Lu, Yingchang; Nelson, Sarah C; Park, Sung-Shim L; Poisner, Hannah; Preuss, Michael H; Richard, Melissa A; Schurmann, Claudia; Setiawan, Veronica W; Sockell, Alexandra; Vahi, Karan; Verbanck, Marie; Vishnu, Abhishek; Walker, Ryan W; Young, Kristin L; Zubair, Niha; Acuna-Alonso, Victor; Ambite, Jose Luis; Barnes, Kathleen C; Boerwinkle, Eric; Bottinger, Erwin P; Bustamante, Carlos D; Caberto, Christian; Canizales-Quinteros, Samuel; Conomos, Matthew P; Deelman, Ewa; Do, Ron; Doheny, Kimberly; Fernandez-Rhodes, Lindsay; Fornage, Myriam; Hailu, Benyam; Heiss, Gerardo; Henn, Brenna M; Hindorff, Lucia A; Jackson, Rebecca D; Laurie, Cecelia A; Laurie, Cathy C; Li, Yuqing; Lin, Dan-Yu; Moreno-Estrada, Andres; Nadkarni, Girish; Norman, Paul J; Pooler, Loreall C; Reiner, Alexander P; Romm, Jane; Sabatti, Chiara; Sandoval, Karla; Sheng, Xin; Stahl, Eli A; Stram, Daniel O; Thornton, Timothy A; Wassel, Christina L; Wilkens, Lynne R; Winkler, Cheryl A; Yoneyama, Sachi; Buyske, Steven; Haiman, Christopher A; Kooperberg, Charles; Le Marchand, Loic; Loos, Ruth J F; Matise, Tara C; North, Kari E; Peters, Ulrike; Kenny, Eimear E; Carlson, Christopher S in Nature (2019). 570(7762) 514–518.
     
  • Imitation und Erkennung von Emotionen bei Autismus-Spektrum-Störungen - eine computerbasierte Analyse des fazialen Emotionsausdrucks. Drimalla, Hanna; Baskow, Irina; Roepke, Stefan; Behnia, Behnoush; Dziobek, Isabel in 12. Wissenschaftliche Tagung Autismus-Spektrum (2019).
     
  • Für bessere Diagnosen und Therapien: Wie Ärzte und KI in der Krebsbehandlung zusammenarbeiten. Schapranow, Matthieu-P. (2019, December).
     
  • MORPHER – A Platform to Support Modeling of Outcome and Risk Prediction in Health Research. Freitas da Cruz, Harry; Bergner, Benjamin; Konak, Orhan; Schneider, Frederic; Bode, Philipp; Lempert, Conrad; Schapranow, Matthieu-P. (2019).
     
  • A Federated In-memory Database System for Life Sciences. Schapranow, Matthieu-P.; others, and in Real-Time Business Intelligence and Analytics. BIRTE 2015, BIRTE 2016, BIRTE 2017, M. Castellanos, P. Chrysanthis, K. Pelechrinis (eds.) (2019). (Vol. 337)
     
  • Diagnosis of obesity and use of obesity biomarkers in science and clinical medicine. Nimptsch, Katharina; Konigorski, Stefan; Pischon, Tobias in Metabolism (2019). 92 61–70.
     
  • Knowledge Distillation from Machine Learning Models for Prediction of Hemodialysis Outcomes. Freitas da Cruz, Harry; Horschig, Siegfried; Nusshag, Christian; Schapranow, Matthieu-P. in International Journal On Advances in Life Sciences (2019). 11(1-2) 33–43.
     
  • Qualitative Comparison of Selected Indel Detection Methods for RNA-Seq Data. Slosarek, Tamara; Kraus, Milena; Schapranow, Matthieu-P; Bottinger, Erwin (2019). 166–177.
     
  • Prediction of Acute Kidney Injury in Cardiac Surgery Patients: Interpretation using Local Interpretable Model-agnostic Explanations. Freitas da Cruz, Harry; Schneider, Frederic; Schapranow, Matthieu-P. (2019). (Vol. 5) 380–387.
     
  • An Information and Communication Platform Supporting Analytics for Elderly Care. Konak, Orhan; Freitas Da Cruz, Harry; Thiele, Marvin; Golla, David; Schapranow, Matthieu-P. (2019).
     
  • Kernel-based tests integrating variant effect predictions from deep learning for genetic association tests of rare variants. Konigorski, Stefan; Monti, Remo; Lippert, Christoph (2019).
     
  • Prediction of circulating adipokine levels based on body fat compartments and adipose tissue gene expression. Konigorski, Stefan; Janke, Jürgen; Drogan, Dagmar; Bergmann, Manuela M.; Hierholzer, Johannes; Kaaks, Rudolf; Boeing, Heiner; Pischon, Tobias in Obesity Facts (2019). 12 590–605.
     
  • A Machine Learning Approach for Non-Invasive Diagnosis of Metabolic Syndrome. Datta, Suparno; Schraplau, Anne; da Cruz, Harry Freitas; Sachs, Jan Philipp; Mayer, Frank; Böttinger, Erwin (2019). 933–940.
     
  • An Information and Communication Platform Supporting Analytics for Elderly Care. Konak, Orhan; Freitas Da Cruz, Harry; Thiele, Marvin; Golla, David; Schapranow, Matthieu-P. (2019).
     

2018

  • Interactive Data Exploration Supporting Elderly Care Planning. Freitas da Cruz, Harry; Gebhardt, Marie; Becher, Felix; Schapranow, Matthieu-P. (2018).
     
  • Prediction of Patient Outcomes after Renal Replacement Therapy in Intensive Care. Freitas da Cruz, Harry; Horschig, Siegfried; Nusshag, Christian; Schapranow, Matthieu-P. (2018).
     
  • HPI-DHC at TREC 2018 Precision Medicine Track. Oleynik, M; Faessler, E; Sasso, A.M; Kappattanavar, A.; Bergner, B.; da Cruz, H.F.; Sachs, J.-P.; Datta, S.; Boettinger, E (2018).
     
  • Analysis of the effects of medication for the treatment of epilepsy by ensemble Iterative Extended Kalman Filtering. Moontaha, Sidratul; Galka, Andreas; Meurer, Thomas; Siniatchkin, Michael (2018). (Vol. 40) 187–190.
     
  • DEAME-Differential Expression Analysis Made Easy. Kraus, Milena; Hesse, Guenter; Slosarek, Tamara; Danner, Marius; Kesar, Ajay; Bhushan, Akshay; Schapranow, Matthieu-P in Heterogeneous Data Management, Polystores, and Analytics for Healthcare (2018). 162–174.
     
  • Kernel-based tests for very rare variants. Konigorski, S; Lippert, C (2018). (Vol. 42) 711.
     
  • Integrating omics and MRI data with kernel-based tests and CNNs to identify rare genetic markers for Alzheimer’s disease. Konigorski, Stefan; Khorasani, Shahryar; Lippert, Christoph (2018).
     
  • Senska - Towards an Enterprise Streaming Benchmark. Hesse, Guenter; Reissaus, Benjamin; Matthies, Christoph; Lorenz, Martin; Kraus, Milena; Uflacker, Matthias (2018). 25–40.
     

2017

  • Anti-adenoviral artificial MicroRNAs expressed from AAV9 vectors inhibit human adenovirus infection in immunosuppressed Syrian hamsters. Schaar, Katrin; Geisler, Anja; Kraus, Milena; Pinkert, Sandra; Pryshliak, Markian; Spencer, Jacqueline F; Tollefson, Ann E; Ying, Baoling; Kurreck, Jens; Wold, William S; others in Molecular Therapy-Nucleic Acids (2017). 8 300–316.
     
  • Olelo: a web application for intuitive exploration of biomedical literature. Kraus, Milena; Niedermeier, Julian; Jankrift, Marcel; Tietboehl, Soeren; Stachewicz, Toni; Folkerts, Hendrik; Uflacker, Matthias; Neves, Mariana in Nucleic acids research (2017).
     
  • Olelo: A Question Answering Application for Biomedicine. Neves, Mariana; Folkerts, Hendrik; Jankrift, Marcel; Niedermeier, Julian; Stachewicz, Toni; Tietböhl, Sören; Kraus, Milena; Uflacker, Matthias (2017).
     
  • The Data Donation Pass: Enabling Sovereign Control of Personal Healthcare Data. Schapranow, Matthieu-P.; Brauer, Janos; Plattner, Hasso (2017).
     
  • A web-based information system for a regional public mental healthcare service network in Brazil. Yoshiura, Vinicius Tohoru; Azevedo-Marques, Joao Mazzoncini; Rzewuska, Magdalena; Vinci, Andre Luiz Teixeira; Sasso, Ariane Morassi; Miyoshi, Newton Shydeo Brandao; Furegato, Antonia Regina Ferreira; Rijo, Rui Pedro Charters Lopes; Del-Ben, Cristina Marta; Alves, Domingos in International journal of mental health systems (2017). 11(1) 1.
     
  • Geometric Algebra Computing for Heterogeneous Systems. Hildenbrand, D.; Albert, Justin; Charrier, P.; Steinmetz, C. in Advances in Applied Clifford Algebras (2017). 27 599–620.
     
  • Die digitale Transformation mitgestalten — Der Datenspendeausweis: Souveräner Umgang mit persönlichen Gesundheitsdaten. Schapranow, Matthieu-P. in Plattform Life Sciences, (H. Garbs, ed.) (2017). (1) 38–39.
     
  • An In-Memory Database Platform for Systems Medicine. Kraus, Milena; Schapranow, Matthieu-P. (2017). 93–100.
     

2016

  • BioMedLAT Corpus: Annotation of the Lexical Answer Type for Biomedical Questions. Neves, Mariana; Kraus, Milena (2016). 49.
     
  • ADRiAS: Acute Disease Risk Assessment System Cruz, H.; Grasnick, S.; Dinger, H. (2016).
     
  • Datenspendeausweis für ­Bürger: Ein Plädoyer für mündige Patienten, die die eigenen Gesundheitsdaten am besten verstehen. Schapranow, Matthieu-P. in Management & Krankenhaus (2016). (9)
     
  • Early Detection of Acute Kidney Injury with Bayesian Networks. Freitas da Cruz, Harry; Grasnick, Bastien; Dinger, Henriette; Bier, Frank; Meinel, Christoph (2016). 29–36.
     
  • IMDBfs: Bridging the Gap between In-Memory Database Technology and File-Based Tools for Life Sciences. Schapranow, Matthieu-P.; Kraus, Milena; Danner, Marius; Plattner, Hasso (2016). 1133–1139.
     
  • Prediction of Health Research Data using In-Memory Database Technology Horschig, Friedrich (2016).
     
  • Towards An Integrated Health Research Process: A Cloud-based Approach. Schapranow, Matthieu-P.; Uflacker, Matthias; Sariyar, Murat; Semler, Sebastian; Fichte, Johannes; Schielke, Dietmar; Ekinci, Kismet; Zahn, Thomas in Proceedings of The IEEE International Conference on Big Data (2016). 2813–2818.
     
  • Real-time Exploration of Healthcare Data using In-Memory Database Technology Rückert, Lars (2016).
     
  • Die In-Memory-Technologie in der personalisierten Medizin. Schapranow, Matthieu-P. (2016, February).
     
  • Geographical Exploration of Key Performance Indicators for Elderly Care Planning Postel, Malek (2016).
     

2015

  • „Surveillance and Outbreak Response Management and Analysis System (SORMAS)“ ermöglicht Kontrolle von Ebola-Infizierten in Westafrika. Denecke, Kerstin; Mall, Sabine; Fähnrich, Cindy; Perscheid, Cindy; Adeoye, Olawunmi Olubunmi; Benzler, Justus; Claus, Hermann; Kirchner, Göran; Richter, Ralph; Schapranow, Matthieu-P.; Schwarz, Norbert; Reigl, Lisa; Tom-Aba, Daniel; Gidado, Saheed; Waziri, Ndadilnasiya Endie; Uflacker, Matthias; Krause, Gérard; Poggensee, Gabriele (2015).
     
  • Surveillance and Outbreak Response Management System (SORMAS) to support the control of the Ebola virus disease outbreak in West Africa. Fähnrich, Cindy; Denecke, Kerstin; Adeoye, Olawunmi; Benzler, Justus; Claus, Hermann; Kirchner, Göran; Mall, Sabine; Richter, Ralph; Schapranow, Matthieu-P.; Schwarz, Norbert G.; Tom-Aba, Daniel; Uflacker, Matthias; Poggensee, Gabriele; Krause, Gerard in Euro Surveillance (2015).
     
  • A Federated In-Memory Database System For Life Sciences. Schapranow, Matthieu-P.; Perscheid, Cindy; Wachsmann, Alf; Siegert, Martin; Bock, Cornelius; Horschig, Friedrich; Liedke, Franz; Brauer, Janos; Plattner, Hasso (2015).
     
  • Facing the Genome Data Deluge: Efficiently Identifying Genetic Variants with In-Memory Database Technology. Fähnrich, Cindy; Schapranow, Matthieu-P.; Plattner, Hasso (2015).
     
  • IT-Aided Business Process Enabling Real-time Analysis of Candidates for Clinical Trials. Schapranow, Matthieu-P.; Perscheid, Cindy; Plattner, Hasso (2015). 67–73.
     
  • An Ontology for TNM Clinical Stage Inference. Massicano, Felipe; Sasso, Ariane; Tomaz, Henrique; Oleynik, Michel; Nobrega, Calebe; Patrao, Diogo FC (2015). (Vol. 1442)
     
  • Recruit-An Ontology Based Information Retrieval System for Clinical Trials Recruitment. Patrao, Diogo FC; Oleynik, Michel; Massicano, Felipe; Sasso, Ariane Morassi (2015). 534–538.
     
  • Implementation and Demonstration of the p-BioSPRE Metabiobank Platform. Dobkwicz, M.; Jüttner, T.; Freitas da Cruz, Harry; Heidtke, K.; Finkenwirth, T.; Kunze, S.; Hänold, S.; Nwankwo, I.; Forgó, N.; Schröder, C.; Graf, N. (2015).
     
  • The Medical Knowledge Cockpit: Real-time Analysis of Big Medical Data Enabling Precision Medicine. Schapranow, Matthieu-P.; Kraus, Milena; Perscheid, Cindy; Bock, Cornelius; Liedtke, Franz; Plattner, Hasso (2015). 770–775.
     

2014

  • High-Performance In-Memory Genome Data Analysis: How In-Memory Database Technology Accelerates Personalized Medicine Schapranow, Matthieu-P.; Plattner, Hasso (2014). 123. Springer.
     
  • Applying In-Memory Technology for Automatic Template Filling in the Clinical Domain. Herbst, Konrad; Fähnrich, Cindy; Neves, Mariana; Schapranow, Matthieu-P. (2014).
     
  • In-Memory Computing Enabling Real-time Genome Data Analysis. Haeger, Franziska; Schapranow, Matthieu-P.; Fähnrich, Cindy; Ziegler, Emanuel; Plattner, Hasso in International Journal on Advances in Life Sciences, Vol 6, Nr 1-2 (2014).
     
  • In-Memory Technology Enables Interactive Drug Response Analysis. Schapranow, Matthieu-P.; Klinghammer, Konrad; Fähnrich, Cindy; Plattner, Hasso (2014).
     
  • Towards Integrating the Detection of Genetic Variants into an In-Memory Database. Fähnrich, Cindy; Schapranow, Matthieu-P.; Plattner, Hasso (2014).
     
  • An Optimized Research Process for Real-time Drug Response Analysis. Schapranow, Matthieu-P.; Klinghammer, Konrad; Fähnrich, Cindy; Plattner, Hasso (2014).
     

2013

  • High-Performance In-Memory Genome Project: A Platform for Integrated Real-Time Genome Data Analysis. Haeger, Franziska; Plattner, Hasso; Schapranow, Matthieu-P. (2013). 5–10.
     
  • Applied In-Memory Technology for High-Throughput Genome Data Processing and Real-time Analysis. Schapranow, Matthieu-P.; Plattner, Hasso; Meinel, Christoph (2013).
     
  • Krebsdatenbank auf Tablet und Smartphone. Schapranow, Matthieu-P. in Best Practice Wireless in der Hauptstadtregion Berlin-Brandenburg, pp. 48-49 (2013).
     
  • Mobile Real-time Analysis of Patient Data for Advanced Decision Support in Personalized Medicine. Schapranow, Matthieu-P.; Plattner, Hasso; Tosun, Cafer; Regenbrecht, Christian (2013).
     
  • HIG – An In-memory Database Platform Enabling Real-time Analyses of Genome Data. Schapranow, Matthieu-P.; Plattner, Hasso (2013). 691–696.
     
  • Applied In-Memory Technology to High Throughput Genome Data Processing. Schapranow, Matthieu-P.; Meinel, Christoph; Plattner, Hasso (2013). 35–42.
     
  • In-Memory Technology Enables History-Based Access Control for RFID-Aided Supply Chains. Schapranow, Matthieu-P.; Plattner, Hasso in The Secure Information Society: Ethical, Legal and Political Challenges, pp. 187-213 (2013).
     
  • Big Data soll Genom-Analysen schneller voranbringen. Schapranow, Matthieu-P.; Meinel, Christoph; Plattner, Hasso in Krankenhaus-IT Journal, p. 26 (2013).
     
  • Real-time Security Extensions for EPCglobal Networks: Case Study for the Pharmaceutical Industry Schapranow, Matthieu-P. (2013). In-Memory Data Management Research, Springer.
     

2012

  • Datenbanktechnologie beflügelt personalisierte Medizin. Schapranow, Matthieu-P.; Meinel, Christoph; Plattner, Hasso in Laborwelt Nr. 4/2012, 13. Jahrgang (2012).
     
  • Blitzschnelle Datenanalysen für die personalisierte Medizin der Zukunft – Interdisziplinäre Impulse aus Potsdam und Berlin. Plattner, Hasso; Meinel, Christoph; Schapranow, Matthieu-P. in Themenbroschüre 2012 Gesundheitsstandort Berlin-Brandenburg (2012).
     
  • Secure RFID-Enablement in Modern Companies: A Case Study of the Pharmaceutical Industry. Müller, Jürgen; Schapranow, Matthieu-P.; Zeier, Alexander; Plattner, Hasso in Handbook of Research on Industrial Informatics and Manufacturing Intelligence: Innovations and Solutions, pp. 507-539, IGI Global (2012).
     

2011

  • Discovery Services in the EPC Network. Schapranow, Matthieu-P.; Zeier, Alexander; Plattner, Hasso; Müller, Jürgen; Lorenz, Martin in Designing and Deploying RFID Applications, pp. 109-130, INTECH Press (2011).
     
  • What are Authentic Pharmaceuticals Worth?. Schapranow, Matthieu-P.; Müller, Jürgen; Zeier, Alexander; Plattner, Hasso in Designing and Deploying RFID Applications, pp. 204-220, INTECH Press (2011).
     
  • A Formal Model for Enabling RFID in Pharmaceutical Supply Chains. Schapranow, Matthieu-P.; Zeier, Alexander; Plattner, Hasso (2011).
     
  • Security Extensions for Improving Data Security of Event Repositories in EPCglobal Networks. Schapranow, Matthieu-P.; Zeier, Alexander; Plattner, Hasso (2011).
     
  • License-based Access Control in EPCglobal Networks. Schapranow, Matthieu-P.; Lorenz, Martin; Zeier, Alexander; Plattner, Hasso (2011).
     
  • Securing EPCglobal Object Name Service -- Privacy Enhancements for Anti-counterfeiting. Schapranow, Matthieu-P.; Zeier, Alexander; Leupold, Felix; Schubotz, Tobias (2011).
     
  • A Distributed EPC Discovery Service based on Peer-to-peer Technology. Lorenz, Martin; Müller, Jürgen; Schapranow, Matthieu-P.; Zeier, Alexander (2011). 1–7.
     
  • Costs of Authentic Pharmaceuticals: Research on Qualitative and Quantitative Aspects of Enabling Anti-counterfeiting in RFID-aided Supply Chains. Zeier, Alexander; Plattner, Hasso; Schapranow, Matthieu-P.; Müller, Jürgen in Personal and Ubiquitous Computing, Volume 16, Issue 3 (2011). 271–289.
     
  • Simulation of RFID-aided Supply Chains: Case Study of the Pharmaceutical Supply Chain. Schapranow, Matthieu-P.; Fähnrich, Cindy; Zeier, Alexander; Plattner, Hasso (2011).
     

2010

  • Real-Time Billing in Smart Grid Infrastructures. Schapranow, Matthieu-P.; Kühne, Ralph; Zeier, Alexander (2010).
     
  • Best Practices for Rigorous Evaluation of RFID Software Components. Müller, Jürgen; Schapranow, Matthieu-P.; Pöpke, Conrad; Urbat, Michaela; Zeier, Alexander; Plattner, Hasso (2010).
     
  • RFID Event Data Processing -- An Architecture for Storing and Searching. Schapranow, Matthieu-P.; Müller, Jürgen; Zeier, Alexander; Plattner, Hasso (2010).
     
  • A Dynamic Mutual RFID Authentication Model Preventing Unauthorized Third Party Access. Schapranow, Matthieu-P.; Zeier, Alexander; Plattner, Hasso (2010).
     
  • CoMoSeR: Cost Model for Security-Enhanced RFID-Aided Supply Chains. Schapranow, Matthieu-P.; Nagora, Mike; Zeier, Alexander (2010).
     
  • Assessment of Communication Protocols in the EPC Network: Replacing Textual SOAP and XML with Binary Google Protocol Buffers Encoding. Schapranow, Matthieu-P.; Geller, Felix; Lorenz, Martin; Müller, Jürgen; Kowark, Thomas; Zeier, Alexander (2010).
     
  • Enabling Real-Time Charging for Smart Grid Infrastructures using In-Memory Databases. Schapranow, Matthieu-P.; Kühne, Ralph; Zeier, Alexander (2010).
     

2009

  • RFID Middleware as a Service - Enabling Small and Medium-sized Enterprises to Participate in the EPC Network. Müller, Jürgen; Schapranow, Matthieu-P.; Helmich, Marco; Enderlein, Sebastian; Zeier, Alexander (2009).
     
  • A Software as a Service RFID Middleware for Small and Medium-sized Enterprises. Müller, Jürgen; Faust, Martin; Schwalb, David; Schapranow, Matthieu-P.; Zeier, Alexander; Plattner, Hasso (2009).
     
  • Data Loading & Caching Strategies in Service-Oriented Enterprise Applications. Schapranow, Matthieu-P.; Krüger, Jens; Borovskiy, Vadym; Zeier, Alexander; Plattner, Hasso (2009).
     
  • Ensuring Service Backwards Compatibility with Generic Web Services. Borovskiy, Vadym; Müller, Jürgen; Schapranow, Matthieu-P.; Zeier, Alexander (2009).
     
  • Integration of RFID Technology is a Key Enabler for Demand-Driven Supply Network. Schapranow, Matthieu-P.; Müller, Jürgen; Krüger, Jens; Hofmann, Paul; Zeier, Alexander in The IUP Journal of Supply Chain Management, Volume 6, Nos. 3 & 4, pp. 57-74 (2009).
     
  • noFilis CrossTalk 2.0 as Device Management Solution, Experiences while Integrating RFID Hardware into SAP Auto-ID Infrastructure. Zeier, Alexander; Schapranow, Matthieu-P.; Krüger, Jens; Uflacker, Matthias; Müller, Jürgen (2009).
     
  • Binary Search Tree Visualization Algorithm. Schapranow, Matthieu-P.; Zeier, Alexander; Borovskiy, Vadym; Müller, Jürgen (2009).
     
  • Security Aspects in Vulnerable RFID-Aided Supply Chains. Schapranow, Matthieu-P.; Müller, Jürgen; Zeier, Alexander; Plattner, Hasso (2009).
     
  • Low-Cost Mutual RFID Authentication Model Using Predefined Password Lists. Schapranow, Matthieu-P.; Müller, Jürgen; Enderlein, Sebastian; Helmich, Marco; Zeier, Alexander (2009).
     

2008

  • Smart Enterprise Widgets: Little Helpers with a Big Impact. Schapranow, Matthieu-P.; Krüger, Jens; Müller, Jürgen in SAP INFO (online) (2008).
     
  • Shared Table Access Pattern Analysis for Multi-Tenant Applications. Krüger, Jens; Grund, Martin; Schaffner, Jan; Schapranow, Matthieu-P.; Bog, Anja (2008).
     
  • Operational Reporting Using Navigational SQL. Grund, Martin; Schaffner, Jan; Schapranow, Matthieu-P.; Bog, Anja; Krüger, Jens (2008).
     
  • HPI Students Learn with SAP Enterprise Services. Schapranow, Matthieu-P.; Krüger, Jens in SAP INFO (online) (2008).
     
  • Combining Advantages - Unified Data Stores in Global Enterprises. Schapranow, Matthieu-P.; Grund, Martin; Krüger, Jens; Schaffner, Jan; Bog, Anja (2008).