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September 17, 2025Statistics in MedicineOpen Access

What Is Fair? Defining Fairness in Machine Learning for Health

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This review examines how fairness impacts ML models in health, highlighting implications for clinical decision-making and health disparities.

Fairness in machine learning impacts clinical decision-making and can prevent existing health disparities.
The review explores multiple fairness notions across group, individual, and causal-based frameworks.
Future research opportunities and challenges for operationalizing fairness in health-focused applications are discussed.
Concern over unfair decision-making in ML models highlights the need for equitable health applications.

Gao et al. (2025) studied this question.

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September 17, 2025Statistics in MedicineOpen Access

View Full Paper

Ask AI

Bookmark

Authors

This review examines how fairness impacts ML models in health, highlighting implications for clinical decision-making and health disparities.

Fairness in machine learning impacts clinical decision-making and can prevent existing health disparities.
The review explores multiple fairness notions across group, individual, and causal-based frameworks.
Future research opportunities and challenges for operationalizing fairness in health-focused applications are discussed.
Concern over unfair decision-making in ML models highlights the need for equitable health applications.

Gao et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark