machine learning
Countries:
Description / Outline
Our research focuses on advancing intelligent algorithms for multi-modal healthcare. We develop new generative and discriminative machine learning methods to enhance diagnostic decision-making, provide real-time guidance to human operators during diagnostic procedures, and explore emerging paradigms such as normative learning to ensure the safety of machine learning and bring its applications to the front lines of patient care.
Our current research questions are:
- Can we democratize rare healthcare expertise through Machine Learning, providing guidance in real-time applications and second reader expertise in retrospective analysis?
- Can we develop normative learning from large populations, integrating imaging, patient records and -omics, leading to data analysis that mimics human decision making?
- Can we provide human interpretability and effective human-machine teamwork of machine decision making to support the ‘right for explanation’ in healthcare?