From Bytes to Bedside and Back: Enhancing Clinical Decision Support with Explainable AI

Samenvatting

Artificial Intelligence (AI) has transformed our daily lives: from car navigation with real-time traffic updates to using ChatGPT for homework and checking smartwatches for sleep quality. In medicine, AI enables more personalised diagnoses and treatments, aiming to reduce side effects, increase efficacy, or even prevent diseases before they manifest. This field, known as precision or personalised medicine, leverages AI to analyse complex data.

The thesis “From Bytes to Bedside and Back: Enhancing Clinical Decision Support with Explainable AI” examines how AI can improve current medical standards. It explores how AI models can help doctors diagnose and treat rare yet deadly diseases, improve patient grouping by considering factors such as age and sex, and assist researchers in generating new scientific hypotheses. The research presented in this thesis aims to contribute to the global efforts of advancing healthcare towards transparency, data-driven practices, and personalised approaches.