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Ensuring Fairness in Machine Learning to Advance Health Equity
4 references·16 citing·40 second hop
Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Ensuring Fairness in Machine Learning to …Mitigating Unwanted Biases with Adversarial Learning (2018)Mitigating Unwanted Biases wi…Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Digital Phenotyping (2017)Digital PhenotypingHealth Care Disparities (2003)Health Care DisparitiesGuiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care (2023)Guiding Principles to Address…Considerations for addressing bias in artificial intelligence for health equity (2023)Considerations for addressing…AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications (2023)AI Fairness in Data Managemen…Evaluation and Mitigation of Racial Bias in Clinical Machine Learning Models: Scoping Review (2022)Evaluation and Mitigation of …Beyond bias and discrimination: redefining the AI ethics principle of fairness in healthcare machine-learning algorithms (2022)Beyond bias and discriminatio…Algorithmic fairness in computational medicine (2022)Algorithmic fairness in compu…Z-Inspection ® : A Process to Assess Trustworthy AI (2021)Z-Inspection ® : A Process to…Structural Racism: The Rules and Relations of Inequity (2021)Structural Racism: The Rules …Machine learning and algorithmic fairness in public and population health (2021)Machine learning and algorith…Ethical Machine Learning in Healthcare (2021)Ethical Machine Learning in H…Advancing health equity with artificial intelligence (2021)Advancing health equity with …Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities (2020)Predictably unequal: understa…Latent bias and the implementation of artificial intelligence in medicine (2020)Latent bias and the implement…An empirical characterization of fair machine learning for clinical risk prediction (2020)An empirical characterization…Measures of Racism, Sexism, Heterosexism, and Gender Binarism for Health Equity Research: From Structural Injustice to Embodied Harm—An Ecosocial Analysis (2019)Measures of Racism, Sexism, H…Artificial intelligence and algorithmic bias: implications for health systems (2019)Artificial intelligence and a…Fairness through awareness (2012)Equality of Opportunity in Supervised Learning (2016)Fairness and Abstraction in Sociotechnical Systems (2019)The NIMH Research Domain Criteria (RDoC) Project: Precision Medicine for Psychiatry (2014)Diez pasos para la construcción de un test (2019)Toward clinical digital phenotyping: a timely opportunity to consider purpose, quality, and safety (2019)Digital interventions for the treatment of depression: A meta-analytic review. 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References

  • 2003Health Care Disparities4,524 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2018Mitigating Unwanted Biases with Adversarial Learning1,387 cited
  • 2017Digital Phenotyping832 cited

Cited by

  • 2021Ethical Machine Learning in Healthcare635 cited
  • 2019Artificial intelligence and algorithmic bias: implications for health systems532 cited
  • 2019Measures of Racism, Sexism, Heterosexism, and Gender Binarism for Health Equity Research: From Structural Injustice to Embodied Harm—An Ecosocial Analysis410 cited
  • 2023Considerations for addressing bias in artificial intelligence for health equity347 cited
  • 2020Predictably unequal: understanding and addressing concerns that algorithmic clinical prediction may increase health disparities274 cited
  • 2023Guiding Principles to Address the Impact of Algorithm Bias on Racial and Ethnic Disparities in Health and Health Care274 cited
  • 2021Machine learning and algorithmic fairness in public and population health219 cited
  • 2020Latent bias and the implementation of artificial intelligence in medicine197 cited
  • 2022Beyond bias and discrimination: redefining the AI ethics principle of fairness in healthcare machine-learning algorithms193 cited
  • 2022Evaluation and Mitigation of Racial Bias in Clinical Machine Learning Models: Scoping Review

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186 cited
  • 2021Structural Racism: The Rules and Relations of Inequity181 cited
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  • 2023AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications155 cited
  • 2021Z-Inspection ® : A Process to Assess Trustworthy AI132 cited
  • 2021Advancing health equity with artificial intelligence117 cited