227-0976-00L Computational Psychiatry & Computational Psychosomatics
| Semester | Frühjahrssemester 2020 |
| Dozierende | K. Stephan |
| Periodizität | jedes Semester wiederkehrende Veranstaltung |
| Lehrsprache | Englisch |
| Kommentar | Number of participants limited to 24. Information for UZH students: Enrolment to this course unit only possible at ETH Zurich. No enrolment to module BMT20002. Please mind the ETH enrolment deadlines for UZH students: Link |
Lehrveranstaltungen
| Nummer | Titel | Umfang | Dozierende | ||||
|---|---|---|---|---|---|---|---|
| 227-0976-00 S | Computational Psychiatry & Computational Psychosomatics Bewilligung der Dozierenden für alle Studierenden notwendig.
**together with University of Zurich** Courses on 04.03.; 11.03.; 08.04.; 29.04.; 27.05.2020. Room: SOF-E-7 (UZH): SOF-E-7 Schönberggasse 1 8001 Zurich https://www.plaene.uzh.ch/SOF/room/SOF-E-07 | 60s Std. |
| K. Stephan |
Katalogdaten
| Kurzbeschreibung | This seminar deals with the development of clinically relevant computational tools and/or their application to psychiatry and psychosomatics. Complementary to the annual Computational Psychiatry Course, it serves to build bridges between computational scientists and clinicians and is designed to foster in-depth exchange, with ample time for discussion |
| Lernziel | Understanding strengths and weaknesses of current trends in the development of clinically relevant computational tools and their application to problems in psychiatry and psychosomatics. |
| Inhalt | This seminar deals with the development of computational tools (e.g. generative models, machine learning) and/or their application to psychiatry and psychosomatics. The seminar includes (i) presentations by computational scientists and clinicians, (ii) group discussion with focus on methodology and clinical utility, (iii) self-study based on literature provided by presenters. |
| Literatur | Literature for additional self-study of the topics presented in this seminar will be provided by the presenters and will be available online at https://www.tnu.ethz.ch/en/teaching.html |
| Voraussetzungen / Besonderes | Participants are expected to be familiar with general principles of statistics (including Bayesian statistics) and have successfully completed the course “Computational Psychiatry” (Course number 227-0971-00L). |
Leistungskontrolle
| Information zur Leistungskontrolle (gültig bis die Lerneinheit neu gelesen wird) | |
Leistungskontrolle als Semesterkurs | |
| ECTS Kreditpunkte | 2 KP |
| Prüfende | K. Stephan |
| Form | benotete Semesterleistung |
| Prüfungssprache | Englisch |
| Repetition | Repetition nur nach erneuter Belegung der Lerneinheit möglich. |
| Zusatzinformation zum Prüfungsmodus | Written assessment: Participants are expected to submit an essay (5 pages max.) that provides a detailed discussion of one of the computational approaches presented in the seminar, with a particular focus on strengths, weaknesses, assumptions and potential for translation into clinical applications. |
Lernmaterialien
| Hauptlink | See TNU website: |
| Es werden nur die öffentlichen Lernmaterialien aufgeführt. | |
Gruppen
| Keine Informationen zu Gruppen vorhanden. |
Einschränkungen
| Allgemein | Bewilligung der Dozierenden für alle Studierenden notwendig |
Angeboten in
| Studiengang | Bereich | Typ | |
|---|---|---|---|
| Biomedical Engineering Master | Wahlfächer der Vertiefung | W |  |
| Biomedical Engineering Master | Wahlfächer der Vertiefung | W | |