The Explainable AI for Health Lab centers its research on one core theme: explainable AI for health.
To drive these advancements, the lab leverages key technical AI components, focusing primarily on:
Computer Vision
Decision Making
With a commitment to explainable systems.
The Explainable AI for Health Lab is dedicated to developing new forms of AI that lead to models that are inherently explainable as much as possible so that physicians and patients can understand why a certain prediction is made.
The lab’s mission and vision are to advance the adoption as well as clinical validation of explainable AI techniques for applications in medicine.
The impact of the lab lies in the development and tailoring of predictive techniques for decision support in palliative oncological care and gynaecological cancer care.
Project 1 – Focuses on advancing GP-GOMEA to jointly optimize constants and the structure of symbolic expression models, as well as hierarchical decompositions of more complex symbolic expression models.
Project 2 – Focuses on combining GP-GOMEA with Bayesian-network learning to jointly identify non-linear feature combinations and a well-fitting Bayesian-network structure.
Project 3 – Focuses on combining GP-GOMEA and Bayesian-network learning with deep learning in order to process multi-modal data, including medical images.
Project 4 – Focuses on enabling uncertainty estimates and counter-factual explanations associated with model predictions.
Project 5 – Focuses on tailoring and validating new techniques and guidelines for clinical use cases in oncology, including palliative care, gynaecological cancer care, and paraganglioma cancer care.
Centrum Wiskunde & Informatica (CWI) is the national research institute for mathematics and computer science.
Leiden University Medical Center (LUMC): As an innovator, the LUMC stands for the continuous improvement of healthcare and the health of all people.
Amsterdam University Medical Centers (AUMC) (location AMC): AUMC is a leading medical center that combines complex high-quality patient care, innovative scientific research, and education of the next generation health care professionals.
