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Explainable AI for Biology and Medicine with Su-In Lee - #642

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

CHAPTER

Unpacking Explainable AI in Medicine

This chapter explores the intricacies of explainable AI (XAI) in the fields of biology and medicine, emphasizing the significance of feature attribution for personalized cancer treatment. It highlights the limitations of current XAI methods and the necessity for more tailored approaches that bridge the gap between theory and practical application. Additionally, the chapter discusses SHAP's contributions to unifying XAI literature and the computational advancements that enhance its effectiveness in real-world scenarios.

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