Workload:
90 h
|
Module Number MEDZ4610 |
Module Title -LLM-assisted Cohort Discovery in Clinical Trials |
Lecture Type(s) Seminar |
|---|---|---|
| ECTS | 3 | |
|
Work load - Contact time - Self study |
Workload:
90 h Class time:
30 h / 2 SWS Self study:
60 h |
|
| Duration | 1 Semester | |
| Frequency | Irregular | |
| Language of instruction | English | |
| Type of Exam | Paper presentation (30 mins) + written report (8 pages) |
|
| Content | The advances made by Large Language Models (LLMs) in Natural Language Processing (NLP) tasks, has renewed interest in many biomedical tasks, including that of clinical trial and patient matching. The seminar covers current research topics in the field of generative AI and its application in clinical trial matching and an optional project on how to create their own cohort discovery model. |
|
| Objectives | Students will critically examine the contributions of a research paper. This course will help them read, assess and discuss research findings through the lens of transparency, explainability, generalization and fairness. They will summarize and evaluate the results of research papers in form of an oral presentation and a written report. |
|
| Allocation of credits / grading |
Type of Class
Status
SWS
Credits
Type of Exam
Exam duration
Evaluation
Calculation
of Module (%) |
|
| Prerequisite for participation | There are no specific prerequisites. | |
| Lecturer / Other | Eickhoff | |
| Literature | - |
|
| Last offered | unknown | |
| Planned for | Wintersemester 2025 | |
| Assigned Study Areas | ||