Hasso-Plattner-Institut

HPI Digital Health Center

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Data Management for Digital Health

Applied Machine Learning for Digital Health

Project Lab

Deep Learning approaches (MAster Thesis)

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Open Topics

Current Master Thesis Topics at DHC:

Evaluating Software Developers’ Code Comprehension Leveraging Low-Cost Psychophysiological Measurements. Contact Fabian Stolp
Machine learning to predict functional effects of genetic variants. Contact Henrike Heyne
Using State-of-the-art Machine Learning for an Early Warning Complication Prediction System. Contact Robin van de Water
Automatic Task Learning. Contact Benjamin Bergner
Self-supervised Multiple Instance Learning. Contact Benjamin Bergner
Correcting Confounders in Deep Image Classification Networks. Contact Benjamin Bergner
Detecting Difficult and Out-of-Distribution Samples in Image Classification. Contact Benjamin Bergner
Gigapixel Medical Image Classification. Contact Benjamin Bergner
Subphenotyping of COVID‐19 associated AKI using deep learning. Contact Girish Nadkarni
Utilizing geographic information system (GIS) and air pollution data along with EHR using machine learning to predict kidney disease progression. Contact Girish Nadkarni
Creating Visual Summaries of Clinical Practice Guidelines with Natural Language Processing. Contact Florian Borchert
Integrative time series analysis: Data from a clinical cross-over study in intermittent fasting Contact Dr.Nico Steckhan

If you have your own ideas for a possible thesis, please feel free to contact us to discuss your thoughts.

Further Topics to take part in our DHC research

Contact

Chair Representatives

Prof. Dr. med. Erwin Böttinger
Professor for Digital Health - Personalized Medicine and Head of Digital Health Center
erwin.boettinger(at)hpi.de
www.hpi.de/boettinger

Office:

Room: G-2.2.22
Phone.: +49-(0)331 5509-164
Fax: +49-(0)331 5509-163
E-mail: office-boettinger(at)hpi.de

Prof. Dr. Bert Arnrich
Professor for Digital Health - Connected Healthcare
www.hpi.de/arnrich

Prof. Dr. Christoph Lippert
Professor for Digital Health & Machine Learning
www.hpi.de/lippert

Office:

Room: G-2.1.22
Phone.: +49-(0)331 5509-4850
Fax: +49-(0)331 5509-4849
E-mail: office-arnrich(at)hpi.de / office-lippert(at)hpi.de

Visiting address:

Campus III Building G2
Rudolf-Breitscheid-Straße 187
14482 Potsdam, Germany

Press and media contact:

HPI Press Departement
presse(at)hpi.de

News

16.09.2022 | HPI-Wissenschaftler entschlüsseln mit neuem Testverfahren weitere Gen-Biomarker

Die Studie des HPI und des Max-Delbrück-Centrums ist in der renommierten Nature Communications erschienen. > Zum Artikel

01.07.2022 | KI-Forschungsgruppe erhält Millionenförderung der DFG

Mithilfe von KI will "DeSBi" Forschenden bessere Methoden zum Erkenntnisgewinn aus strukturierten biomedizinischen Daten … > Zum Artikel

03.06.2021 | Harvard Business School expert appointed new HPI Visiting Professor

28.04.2021 | Neue Podcast-Folge über die digitale Früherkennung von Zwangsstörungen

31.03.2021 | Künstliche Intelligenz im Einsatz für den Rettungsdienst

Hasso Plattner Institute for Digital Health at Mount Sinai (HPI·MS)

In March 2019, the Hasso Plattner Institute for Digital Health at Mount Sinai ( HPI·MS ) was formed as the result of a cooperation agreement between the Mount Sinai Health System (MSHS) in New York City and the Hasso Plattner Institute (HPI). www.hpims.org/