|Dozierende||Dorothee Bentz (firstname.lastname@example.org, BeurteilerIn)|
|Inhalt||The workshop will be given by Prof. Dr. Katharina Schultebraucks, Co-Director of the Computational Psychiatry Program and Associate Professor in the Department of Psychiatry and in the Division of Healthcare Delivery Science, Department of Population Health at NYU Grossmann School of Medicine.
This course provides an introduction to methodological aspects of the practical application of predictive modeling and data science to support clinical decision-making. It focuses on the clinical application with concrete use-cases to call attention to key methodological challenges and their solution. The course encourages critical thinking to systematically address questions of how data science can positively influence clinical decision-making and how approaches can be implemented. Students will en-gage with practical examples of data science approaches for clinical decision-making published in the scientific literature.
|Lernziele||By the end of the course, students will be able to:
1. Identify common methodological challenges in the practical application of predictive modeling
2. Identify potential solutions to methodological challenges throughout the design, implementation, and evaluation of predictive models in medicine and public health
3. Define the role of data science for clinical decision-making such as diagnosis, prognosis, targeted treatment allocation, and risk-stratified prevention strategies.
4. Understand epidemiological and methodological aspects of study design for prediction model-ing
5. Understand the importance of and the criteria for the critical appraisal of diagnostic and prognostic models published in scientific journals
6. Successfully plan the scientific sound design and implementation of a data science project to positively influence clinical decision-making
|Literatur||- Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating, Second Edition, by Ewout W. Steyerberg, Springer, 2019. (https://link.springer.com/book/10.1007/978-3-030-16399-0)
Fundamentals of Clinical Data Science, by Pieter Kubben, Michel Dumontier, and Andre Dekker, Springer, 2019. (https://link.springer.com/book/10.1007/978-3-319-99713-1)
- An Introduction to Statistical Learning with Applications in R, by Gareth James, Daniela Witten, Tre-vor Hastie, and Robert Tibshirani, Springer, 2013. (http://www-bcf.usc.edu/~gareth/ISL/)
- Applied Predictive Modeling, by Max Kuhn and Kjell Johnson, Springe, 2013. (https://link.springer.com/book/10.1007/978-1-4614-6849-3)
|Bemerkungen||Priority will be given to PhD students from the doctoral program HI-PSY. Places will be given according to this selection criteria:
1) PhD students from the doctoral program HI-PSY
2) PhD students of other specializations of the Faculty of Psychology
3) PhD students of other faculties of the University of Basel
HI-PSY rules for withdrawal, absence, or partial course attendance:
If you cannot attend a workshop that you have signed up for, please cancel your course registration as soon as possible by sending an e-mail to email@example.com. This will allow other PhD students interested in the course to move up from the waiting list. After the university’s official registration period has ended, cancelled course will be assessed with NE. Course registrations can be can-celled until one week before the workshops begins. In the case of late cancellations, participants will not be considered for course registration in the next three months of the lecture periods and will be removed from the registration list of any course they have signed up during these three upcoming months of the lecture periods.
If an urgent, unforeseeable, or inevitable event before or during the course prevents a participant from attending, a written and substantiated withdrawal request that includes appropriate documentation (e.g. a doctor’s note) must be submitted to firstname.lastname@example.org within two days of the workshop and without being prompted. The program director decides on the approval of the withdrawal request.
ECTS-points are awarded only for 100% course attendance.
|Teilnahmebedingungen||The workshop is offered by the doctoral program HI-PSY. PhD students who are not part of the doctoral program HI-PSY please apply for admission to the workshop before course registration by send-ing an e-mail to the program director Prof. Dr. Jens Gaab (email@example.com).|
|Einsatz digitaler Medien||Online-Veranstaltung|
|Datum||20.11.2023 – 27.11.2023|
|Montag 20.11.2023||14.00-18.00 Uhr||- Online Präsenz -, --|
|Montag 27.11.2023||14.00-18.00 Uhr||- Online Präsenz -, --|
Doktorat Psychologie: Empfehlungen (Promotionsfach Psychologie)
|An-/Abmeldung zur Leistungsüberprüfung||Anm.: Belegen Lehrveranstaltung; Abm.: stornieren|
|Skala||Pass / Fail|
|Wiederholtes Belegen||beliebig wiederholbar|
|Zuständige Fakultät||Fakultät für Psychologie, firstname.lastname@example.org|
|Anbietende Organisationseinheit||Fakultät für Psychologie|