Artificial intelligence and algorithmic bias: implications for health systems

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Abstract

Algorithmic bias occurs when the application of an algorithm compounds existing inequities in socioeconomic status, race, ethnic background, religion, gender, disability or sexual orientation to amplify them and adversely impact equity in health systems.

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Authors

Trishan Panch

Harvard University

Heather Mattie

Harvard University

Rifat Atun

Boston University

Journals

Journal of Global Health

Actions

Institutions

Harvard University

Harvard Global Health Institute

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Panch et al. (Sun,) studied this question.

synapsesocial.com/papers/6a0e9c308720ffe3c104521d — DOI: https://doi.org/10.7189/jogh.09.020318

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Also consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

Safety of patient-facing digital symptom checkers· 2018 · 204 citations
Ensuring Fairness in Machine Learning to Advance Health Equity· 2018 · 1,151 citations
Untitled· 1,660 citations
Artificial intelligence, machine learning and health systems· 2018 · 629 citations
A clinically applicable approach to continuous prediction of future acute kidney injury· 2019 · 1,092 citations

Artificial intelligence and algorithmic bias: implications for health systems

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Journals

Actions

Institutions

References and Citations

Citation Network

Connected Papers

Discussion

Cite this study

Also consider

Also consider