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Artificial Intelligence in Medicine (IN2403)

Course 0000000960 in WS 2022/3

General Data

Course Type lecture
Semester Weekly Hours 4 SWS
Organisational Unit Informatics 31 - Chair of Artificial Intelligence in Healthcare and Medicine (Prof. Rückert) (Joint Appointment between Department of Medicine und Department of Informatics)
Lecturers Daniel Rückert
Julia Schnabel
Dates Thu, 16:00–18:00, EI-HS Garching
Mon, 16:00–18:00, EI-HS Garching

Assignment to Modules

Further Information

Courses are together with exams the building blocks for modules. Please keep in mind that information on the contents, learning outcomes and, especially examination conditions are given on the module level only – see section "Assignment to Modules" above.

additional remarks • Introduction: Clinical motivation, clinical data, clinical workflows • ML for medical imaging • Data curation for medical applications • Domain shift in medical applications: Adversarial learning and Transfer learning • Self-supervised learning and unsupervised learning • Learning from sparse and noisy data • ML for unstructured and multi-modal clinical data • NLP for clinical data • Bayesian approaches to deep learning and uncertainty • Interpretability and explainability • Federated learning, privacy-preserving ML and ethics • ML for time-to-event modeling, survival models • ML for differential diagnosis and stratification • Clinical applications in pathology/radiology/omics
Links E-Learning course (e. g. Moodle)
TUMonline entry

Equivalent Courses (e. g. in other semesters)

WS 2021/2 Artificial Intelligence in Medicine (IN2403) Rückert, D. Schnabel, J. Tue, 16:15–17:45, virtuell
Thu, 16:15–17:45
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