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Clinicians Could Be Fooled by Biased AI, Despite Explanations

Clinicians Could Be Fooled by Biased AI, Despite Explanations
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United statesSarah jabbourKelly malcom derek smithStephanie shepardDavid fouheyEllaa kazerooniJenna wiensMichael sjodingNikola banovicUniversity of michiganHealth lab podcastBlood instituteNational heartDrug administrationCollege of engineeringHealth lab

Artificial Intelligence Models Improve Clinicians Diagnostic Accuracy

Standard artificial intelligence (AI) models improve diagnostic accuracy, but systematically biased AI models reduce this accuracy.

Ann arborUnited statesSarah jabbourUniversity of michiganJournal of the american medical associationHealthday newsAmerican medical

If You Want Your Stocking Stuffed on Christmas, Go Ahead : What We Heard This Week

Quotable quotes heard by <em>MedPage Today</em>'s reporters

Ann arborUnited statesNew south walesBoca ratonWestern australiaNew yorkJustin dubinZiyad al alyNehal vadhanKatherine klamerAdrian traegerDaniel waintraubSarah jabbourUniversity of sydneyGastro health boca ratonUniversity of toronto

Explanations Don t Help Clinicians Spot Biased AI

Biased AI predictions tanked diagnostic accuracy, and model explanations didn't bring it back up

New havenUnited statesRohan kheraSarah jabbourMichael sjodingMichael depeauUniversity of michiganUniversity of michigan health in ann arborYale school of medicineMichigan healthAnn arborMedpage todayYale school

AI in healthcare double-edged sword , can fool clinicians with data: Study

AI models in health care are a double-edged sword, with models improving diagnostic decisions for some demographics, but worsening decisions for others when the model has absorbed biased medical data, suggests a study.Given the very real life .

United statesNew yorkMichael sjodingSarah jabbourCollege of engineeringUniversity of michiganAssociate professor

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