Data analysis and AI-modelling for disease outcome prediction
AI is reshaping every aspect of science. In clinical settings, vast data are generated every day. These data have great potential to help answer clinical questions and facilitate decision-making. For example, is a patient likely to achieve the desired outcome if they take a certain medication? Is a side effect likely to occur? AI models may help to make such predictions by learning from existing patient data.
Research question: Can AI help to predict disease outcomes to facilitate clinical decision-making?
Research design: This research will mainly use clinical data from hospital electronic medical records. We will explore data processing and cleaning methods, and train different machine-learning models that can predict certain clinical outcomes. The medical domain is most likely inflammatory bowel diseases, but other domains are possible.
Methods for data collection: Data are either provided by other parties or collected directly via hospital electronical medical records.
Potential supervisor: Jiaxu Zhang, PhD Student at Maastricht University (jiaxu.zhang@maastrichtuniversity.nl)
Required skills: basic understanding of statistics and machine-learning, especially in regression analysis, Python programming.
Time period: 2026-2027
Location: Maastricht Randwyck