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Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning.

, , , , , and . J. Am. Medical Informatics Assoc., 27 (12): 2024-2027 (2020)

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What Clinicians Want: Contextualizing Explainable Machine Learning for Clinical End Use., , , and . MLHC, volume 106 of Proceedings of Machine Learning Research, page 359-380. PMLR, (2019)An integration engineering framework for machine learning in healthcare., , , , , , , , , and 3 other author(s). Frontiers Digit. Health, (2022)What's fair is... fair? Presenting JustEFAB, an ethical framework for operationalizing medical ethics and social justice in the integration of clinical machine learning: JustEFAB., , , , , , , , , and 5 other author(s). FAccT, page 1505-1519. ACM, (2023)Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning., , , , , and . J. Am. Medical Informatics Assoc., 27 (12): 2024-2027 (2020)How to validate Machine Learning Models Prior to Deployment: Silent trial protocol for evaluation of real-time models at ICU., , , , , , , , , and 1 other author(s). CHIL, volume 174 of Proceedings of Machine Learning Research, page 169-182. PMLR, (2022)When Your Only Tool Is A Hammer: Ethical Limitations of Algorithmic Fairness Solutions in Healthcare Machine Learning., , , and . AIES, page 109. ACM, (2020)