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Enabling Fairness in Healthcare Through Machine Learning
16 references·2 citing·39 second hop
Enabling Fairness in Healthcare Through Machine Learning (2022)Enabling Fairness in Healthcare Through M…Algorithmic bias: Senses, sources, solutions (2021)Algorithmic bias: Senses, sou…Transparency in Complex Computational Systems (2020)Transparency in Complex Compu…Algorithmic Fairness: Choices, Assumptions, and Definitions (2020)Algorithmic Fairness: Choices…Algorithmic bias: on the implicit biases of social technology (2020)Algorithmic bias: on the impl…The Principles and Limits of Algorithm-in-the-Loop Decision Making (2019)The Principles and Limits of …Improving Fairness in Machine Learning Systems (2019)Improving Fairness in Machine…Dissecting racial bias in an algorithm used to manage the health of populations (2019)Dissecting racial bias in an …Ensuring Fairness in Machine Learning to Advance Health Equity (2018)Ensuring Fairness in Machine …Algorithms of Oppression (2018)Algorithms of OppressionFair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments (2017)Fair Prediction with Disparat…Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy (2016)Weapons of Math Destruction: …Inherent Trade-Offs in the Fair Determination of Risk Scores (2016)Inherent Trade-Offs in the Fa…Responsibility for Implicit Bias (2012)Responsibility for Implicit B…Evidence-Based Policy (2012)Evidence-Based PolicyRacial and Ethnic Disparities in Pain: Causes and Consequences of Unequal Care (2009)Racial and Ethnic Disparities…The Unequal Burden of Pain: Confronting Racial and Ethnic Disparities in Pain (2003)The Unequal Burden of Pain: C…Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study (2024)Health equity assessment of m…Ethical assessments and mitigation strategies for biases in AI-systems used during the COVID-19 pandemic (2023)Ethical assessments and mitig…Research on the Provider Contribution to Race/Ethnicity Disparities in Medical Care (2002)Moving Upstream (2008)Differences in sleep between black and white adults: an update and future directions (2015)Racial and Ethnic Differences in the Experience and Treatment of Noncancer Pain (2019)From race-based to race-conscious medicine: how anti-racist uprisings call us to act (2020)The Social System (1951)Race, Socioeconomic Status, and Health The Added Effects of Racism and Discrimination (1999)Unequal treatment: confronting racial and ethnic disparities in health care (2003)Cancer, Culture, and Health Disparities: Time to Chart a New Course? (2010)Racial Bias in Perceptions of Others’ Pain (2012)Fairness through awareness (2012)Equality of Opportunity in Supervised Learning (2016)Fairness and Abstraction in Sociotechnical Systems (2019)A Survey on Bias and Fairness in Machine Learning (2021)Health Care Disparities (2003)Mitigating Unwanted Biases with Adversarial Learning (2018)Artificial intelligence and algorithmic bias: implications for health systems (2019)Measures of Racism, Sexism, Heterosexism, and Gender Binarism for Health Equity Research: From Structural Injustice to Embodied Harm—An Ecosocial Analysis (2019)Ethical Machine Learning in Healthcare (2021)Big Data's Disparate Impact (2014)Semantics derived automatically from language corpora contain human-like biases (2017)Decolonial AI: Decolonial Theory as Sociotechnical Foresight in Artificial Intelligence (2020)Addressing bias in big data and AI for health care: A call for open science (2021)Algorithmic Bias in Education (2021)A theory of justice original editionGender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018)Towards a standard for identifying and managing bias in artificial intelligence (2022)Bias and Unfairness in Machine Learning Models: A Systematic Review on Datasets, Tools, Fairness Metrics, and Identification and Mitigation Methods (2023)Fairness in Machine Learning: A Survey (2023)The global landscape of AI ethics guidelines (2019)On the Opportunities and Risks of Foundation Models (2021)Algorithms at Work: The New Contested Terrain of Control (2019)When data is capital: Datafication, accumulation, and extraction (2019)What Do Platforms Do? Understanding the Gig Economy (2020)AI Fairness 360: An extensible toolkit for detecting and mitigating algorithmic bias (2019)Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019)Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources, Impacts, and Mitigation Strategies (2023)Algorithmic bias: review, synthesis, and future research directions (2021)Taxonomy of Risks posed by Language Models (2022)
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References

  • 2019Dissecting racial bias in an algorithm used to manage the health of populations7,086 cited
  • 2018Algorithms of Oppression2,709 cited
  • 2016Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy2,335 cited
  • 2017Fair Prediction with Disparate Impact: A Study of Bias in Recidivism Prediction Instruments2,157 cited
  • 2018Ensuring Fairness in Machine Learning to Advance Health Equity1,334 cited
  • 2003The Unequal Burden of Pain: Confronting Racial and Ethnic Disparities in Pain1,248 cited
  • 2016Inherent Trade-Offs in the Fair Determination of Risk Scores942 cited
  • 2009Racial and Ethnic Disparities in Pain: Causes and Consequences of Unequal Care898 cited
  • 2019Improving Fairness in Machine Learning Systems776 cited
  • 2020Algorithmic Fairness: Choices, Assumptions, and Definitions687 cited
  • 2012Evidence-Based Policy671 cited
  • 2019The Principles and Limits of Algorithm-in-the-Loop Decision Making386 cited
  • 2021Algorithmic bias: Senses, sources, solutions274 cited
  • 2012Responsibility for Implicit Bias238 cited
  • 2020Algorithmic bias: on the implicit biases of social technology234 cited

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  • 2020Transparency in Complex Computational Systems193 cited
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    • 2024Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study34 cited
    • 2023Ethical assessments and mitigation strategies for biases in AI-systems used during the COVID-19 pandemic26 cited