References

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• 2015Certifying and Removing Disparate Impact1,827 cited
• 2018Ensuring Fairness in Machine Learning to Advance Health Equity1,334 cited
• 2020Fairness in Machine Learning299 cited
• 2020Ethical limitations of algorithmic fairness solutions in health care machine learning290 cited
• 2019Mathematical Notions vs. Human Perception of Fairness179 cited
• 2020Investigating Bias and Fairness in Facial Expression Recognition174 cited
• 2021Comparison of Methods to Reduce Bias From Clinical Prediction Models of Postpartum Depression116 cited
• 2017Addressing bias in machine learning algorithms: A pilot study on emotion recognition for intelligent systems100 cited
• 2020Empirical observation of negligible fairness-accuracy trade-offs in machine learning for public policy97 cited
• 2018A physiological signal-based method for early mental-stress detection96 cited
• 2020TILES-2018, a longitudinal physiologic and behavioral data set of hospital workers90 cited
• 2018Contemplating Visual Emotions: Understanding and Overcoming Dataset Bias85 cited
• 2019Taking Advantage of Multitask Learning for Fair Classification64 cited
• 2021