Student's Corner

Georg von Arnim gives insights into personalized drug recommendation via in-context learning on graph data, the topic of his recently submitted master's thesis.

Mohamed Aborageh shares a preview of his upcoming paper, demonstrating how genetic data can be used to assess the causal effect of different comorbidities on the development of dementia in Parkinson's patients.

Konrad Gerischer presents his Master's thesis about differences in the expression of immune system-related genes between Alzheimer's patients and healthy controls.

Joud Odeh talks about her Master's thesis in which she analyzed the sleep behavior of patients with different stages of Alzheimer's disease.

PhD candidate Jonas describes how dynamic ensembles can help reduce bias in short-term forecasts in pandemic situations. This work is part of the AIOLOS project.

Master student Yihao Wang explains how he improved Natural Language Processing (NLP) models by infusing prior knowledge from ontologies.

PhD student Diego Valderrama explains how hybrid models can be used as an interpretable alternative to black-box machine learning approaches for pharmacokinetics modeling.

Jackrite To presents his work on validating gait parameters to monitor the progression of Parkinson's disease better and to improve personalized treatment.

Master student Srividhya Sainath analyzes genetic profiles of Parkinson's disease patients to explore subtypes.

Master student Johanna Driever explains how she used a natural language processing model in combination with electronic health records to predict Parkinson’s disease.