Machine Learning in Healthcare - From Interpretability to Human-Machine Partnership

Explore the transformative potential of machine learning in healthcare through this 47-minute conference talk by Mihaela van der Schaar from the University of Cambridge. Delve into the challenges of interpretability in complex "black box" machine learning models and discover a unique framework for developing interpretable models based on user needs. Examine real-world examples from extensive research and interdisciplinary discussions with clinical professionals. Investigate exciting possibilities for applying interpretability and machine learning to understand and enhance human decision-making. Gain insights into the broader context of trustworthy artificial intelligence, including accountability, fairness, privacy, and safety. Suitable for a wide audience, including those with little to no prior knowledge of machine learning or healthcare.

Machine learning in healthcare: From interpretability to a new human-machine partnership