Trustworthy Computing for Biomedical Challenges

Abstract

This tutorial focuses on the role of trustworthy machine learning techniques in transforming healthcare through the analysis of vast and intricate medical data. It covers the core techniques of accuracy, robustness, fairness, and interpretability in computational medicine, including their challenges and potential for future development. The tutorial aims to provide a comprehensive overview of trustworthy machine learning techniques that can be adopted in healthcare and is suitable for audiences with a background in biomedicine and machine learning. By emphasizing the importance of trustworthy machine learning in healthcare, the tutorial aims to offer insights into how these techniques can lead to more precise diagnoses and treatment regimes.

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