Hasso-Plattner-Institut
Prof. Dr. Erwin Böttinger
  
 

Ariane Morassi Sasso

Research Assistant, PhD Candidate

Phone: + 49- (0) 331 5509-4827


Room: G-2.2 30/31


Email: ariane.morassi-sasso(at)hpi.de


Web: Linkedin, Research Gate, GitHub, Twitter

Research Topics

  • Representation and Integration of Health-Related Data
  • Machine Learning Applied to Healthcare
  • Digital Biomarkers

Master Thesis and Master Project Supervisions

Master Thesis

Felix Musmman (2020)

A web platform for analyzing multimodal sensor data in the context of digital health

GitHub

Paper Published at ICHI 2020 (Link)

 

Hendrik Folkerts (2021)

Blood Pressure Estimation using Photoplethysmography

Margaux Gatrio (2021 - Ongoing)

Personalized Risk Score Prediction for Intensive Care Patients

 

Master Projects

Wearables for monitoring and driving lifestyle changes (2019)

Students: Hendrik Folkerts, Arne Herdick, Corina Jaschek, Pit Wegner

Supervisors: Ariane Sasso, Suparno Datta, Lin Zhou, Justin Albert and Jonas Chromik

Project Proposal: Link

HPI only internal video: Link

 

Using Machine Learning Algorithms to predict Hypertension based on Electronic Health Records (2019/2020)

Students: Nina Kiwit, Jonas Cremerius, Margaux Gatrio, Melanie Hackl (Students)

Supervisors: Suparno Datta, Ariane Sasso, Dr. Girish Nadkarni, Prof. Dr. Erwin Böttinger (supervisors)

Project Proposal: Link

Video: Link

Conferences, Events and Reviews

Presenter

 

Panelist

Bachelor, Master ... and then PhD? Academic work in computer science

 

Reviewer

  • American Medicial Informatics Association (AMIA) Symposium 2020
  • Grace Hopper Conference (GHC) 2020 - Artificial Intelligence
  • ACM Transactions on Computing for Healthcare 2020

Awards

Best Student Paper Award at AIME 2020 (Artificial Intelligence in Medicine)

Morassi Sasso, A., Datta, S., Jeitler, M., Steckhan, N., Kessler, C. S., Michalsen, A., Bert, A., Boettinger, E.: HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population. Proceedings of AIME (2020).

Paper | MedRxiv Link | Presentation

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Best Student Paper Award in Track (Making Digital Inclusive – Blending the Local and the Global) at ICIS 2020 (International Conference on Information Systems)

Schmitt, Franziska; Sundermeier, Janina; Bohn, Nicolai; and Morassi Sasso, Ariane, “Spotlight on Women in Tech: Fostering an Inclusive Workforce when Exploring and Exploiting Digital Innovation Potentials” (2020). ICIS 2020 Proceedings. 6.

Paper | ResearchGate

Publications

  • 1.
    Musmann, F., Sasso, A., Arnrich, B.: ALPS: A Web Platform for Analysing Multimodal Sensor Data in the Context of Digital Health. 2020 IEEE International Conference on Healthcare Informatics (ICHI). pp. 1–12. IEEE Computer Society, Los Alamitos, CA, USA (2020).
     
  • 2.
    Morassi Sasso, A., Datta, S., Jeitler, M., Steckhan, N., Kessler, C.S., Michalsen, A., Arnrich, B., Böttinger, E.: HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population. In: Michalowski, M. and Moskovitch, R. (eds.) Artificial Intelligence in Medicine. AIME 2020. Lecture Notes in Computer Science. Springer (2020).
     
  • 3.
    Schmitt, F., Sundermeier, J., Bohn, N., Morassi Sasso, A.: Spotlight on Women in Tech: Fostering an Inclusive Workforce when Exploring and Exploiting Digital Innovation Potentials. ICIS Proceedings (2020).
     
  • 4.
    Sasso, A.M., Datta, S., Jeitler, M., Steckhan, N., Kessler, C.S., Michalsen, A., Arnrich, B., Boettinger, E.: HYPE: Predicting Blood Pressure from Photoplethysmograms in a Hypertensive Population. International Conference on Artificial Intelligence in Medicine. pp. 325–335. Springer (2020).
     
  • 5.
    Morassi Sasso, A., Datta, S., Pfitzner, B., Zhou, L., Steckhan, N., Boettinger, E., Arnrich, B.: Unobtrusive Measurement of Blood Pressure During Lifestyle Interventions. Proceedings of the 13th EAI International Conference on Pervasive Computing Technologies for Healthcare - Demos and Posters. EAI, Trento (2019).
     
  • 6.
    Oleynik, M., Faessler, E., Sasso, A., Kappattanavar, A., Bergner, B., da Cruz, H., Sachs, J.-P., Datta, S., Boettinger, E.: HPI-DHC at TREC 2018 Precision Medicine Track. Presented at the (2018).
     
  • 7.
    Yoshiura, V.T., Azevedo-Marques, J.M., Rzewuska, M., Vinci, A.L.T., Sasso, A.M., Miyoshi, N.S.B., Furegato, A.R.F., Rijo, R.P.C.L., Del-Ben, C.M., Alves, D.: A web-based information system for a regional public mental healthcare service network in Brazil. International journal of mental health systems. 11, 1 (2017).
     
  • 8.
    Patrao, D.F., Oleynik, M., Massicano, F., Sasso, A.M.: Recruit-An Ontology Based Information Retrieval System for Clinical Trials Recruitment. MedInfo. pp. 534–538 (2015).
     
  • 9.
    Massicano, F., Sasso, A., Tomaz, H., Oleynik, M., Nobrega, C., Patrao, D.F.: An Ontology for TNM Clinical Stage Inference. ONTOBRAS (2015).