Last January, Antonio López presented his doctoral thesis titled “Clustering and Subgroup Discovery for Patient Phenotyping“.
What’s about…
This doctoral thesis, situated in the field of Medical AI, investigates the application of Machine Learning (ML) techniques, specifically clustering and subgroup discovery (SD), to support the patient phenotyping process in the context of antimicrobial resistance (AMR).
The study proposes new ML methods for generating and identifying patient phenotypes that are both useful and readable for clinicians. Key contributions include the development of a public Python library for SD algorithms and a new methodology that involves clinical experts in the phenotyping process. The research demonstrates the effectiveness of these approaches in addressing the AMR problem, using the MIMIC-III database to ensure reproducibility.
Congratulations to Antonio on this great achievement!
