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Ethical limitations of algorithmic fairness solutions in health care machine learning
6 references·16 citing·47 second hop
Ethical limitations of algorithmic fairness solutions in health care machine learning (2020)Ethical limitations of algorithmic fairne…Dissecting racial bias in an algorithm used to manage the health of populations (2019)Dissecting racial bias in an …Assessing risk, automating racism (2019)Assessing risk, automating ra…The Measure and Mismeasure of Fairness (2018)The Measure and Mismeasure of…Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement (2015)Transparent Reporting of a mu…Social determinants of health inequalities (2005)Social determinants of health…Social determinants of health inequalities (2005)Social determinants of health…A scoping review and evidence gap analysis of clinical AI fairness (2025)A scoping review and evidence…Conversational AI and equity through assessing GPT-3’s communication with diverse social groups on contentious topics (2024)Conversational AI and equity …Challenges and opportunities in translating ethical AI principles into practice for children (2024)Challenges and opportunities …Humans perceive warmth and competence in artificial intelligence (2023)Humans perceive warmth and co…Friend or Foe? 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References

  • 2019Dissecting racial bias in an algorithm used to manage the health of populations7,086 cited
  • 2005Social determinants of health inequalities5,069 cited
  • 2015Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD): The TRIPOD Statement3,229 cited
  • 2005Social determinants of health inequalities1,531 cited
  • 2018The Measure and Mismeasure of Fairness445 cited
  • 2019Assessing risk, automating racism377 cited

Cited by

  • 2021Machine learning and algorithmic fairness in public and population health219 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 Review186 cited
  • 2020An empirical characterization of fair machine learning for clinical risk prediction165 cited
  • 2021Fairness for Unobserved Characteristics: Insights from Technological Impacts on Queer Communities131 cited
  • 2021Comparison of Methods to Reduce Bias From Clinical Prediction Models of Postpartum Depression116 cited
  • 2023Friend or Foe? Teaming Between Artificial Intelligence and Workers with Variation in Experience114 cited
  • 2020Patient safety and quality improvement: Ethical principles for a regulatory approach to bias in healthcare machine learning

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111 cited
  • 2021A Proposed Framework on Integrating Health Equity and Racial Justice into the Artificial Intelligence Development Lifecycle108 cited
  • 2023Humans perceive warmth and competence in artificial intelligence96 cited
  • 2022Tackling bias in AI health datasets through the STANDING Together initiative82 cited
  • 2022Peeking into a black box, the fairness and generalizability of a MIMIC-III benchmarking model73 cited
  • 2021Review of study reporting guidelines for clinical studies using artificial intelligence in healthcare66 cited
  • 2025A scoping review and evidence gap analysis of clinical AI fairness62 cited
  • 2024Conversational AI and equity through assessing GPT-3’s communication with diverse social groups on contentious topics46 cited
  • 2024Challenges and opportunities in translating ethical AI principles into practice for children42 cited