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AI for Health

Thema: AI for Health

DozentIn(en): Prof. Roland Eils, Julius Upmeier zu Belzen, Thore Buergel

Maximale Teilnehmerzahl: 4

Zeitraum/Vorbesprechungstermin: nach Absprache

Ort: Digital (A), BIH, Kapelle-Ufer 2 (B)

Kurze inhaltliche Beschreibung:

Project: Machine Learning in Medicine: from idea to tool

  • Learn the fundamentals of developing, training and testing deep learning models in the medical domain
  • Learn about relevant metrics for evaluation and benchmarking and potential biases to watch out for
  • Work on integrating the developed and evaluated models into usable (web) tool

Quantitative Aufteilung: (in %)

Praktische Programmierarbeit: 75%
Soft Skills: 25%

Verwendete Programmiersprache(n): Python (>90%), maybe some javascript for web app

Schwierigkeitsgrad (Acht Sterne verteilt auf drei Bereiche):

A Programmieren ****
B Biologie/Chemie *
C Projektmanagement ***

Erforderliche Vorkenntnisse:

  • Experience with the Python programming language
  • Fundamental understanding of “What is machine learning"
  • Preferably prior experience with PyTorch or other DL-Libraries
  • Understanding of neural networks and preferably experience with deep learning

Kontaktadresse, Webseite/Link:

Thore Buergel
Julius Upmeier zu Belzen
https://www.hidih.org/research/ailslab 

eVV