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Achieving Clinical AI Fairness Requires Multidisciplinary Collaboration

Achieving Clinical AI Fairness Requires Multidisciplinary Collaboration
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Shania kennedyOphthalmology visual sciences academic clinical programmeSinghealth ai officeCentre for quantitative medicineNational university of singaporeAchieving clinicalGetty imagesDigital medicineDuke national universityMedical schoolNing yilinQuantitative medicineDaniel tingVisual sciences academic clinicalMayo clinic

Ensuring fairness of AI in healthcare requires cross-disciplinary collaboration

Ensuring fairness of AI in healthcare requires cross-disciplinary collaboration
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United statesLiu mingxuanLionel cheng timLiu nanProgramme atOphthalmology visual sciences academic clinical programmeDepartment of diagnostic radiology at singaporeSinghealth ai officeMedicine biostatistics health data science programmeHealth services systems researchSingapore eye research instituteAi future health system departmentSingapore national eye centreCentre for quantitative medicineAcademic medical centreDepartment of emergency medicine

Ensuring fairness of AI in healthcare requires cross-disciplinary collaboration

Ensuring fairness of AI in healthcare requires cross-disciplinary collaboration
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United statesLiu nanLionel cheng timLiu mingxuanHealth services systems researchOphthalmology visual sciences academic clinical programmeUniversity of antwerpSingapore national eye centreDepartment of emergency medicineAi future health system departmentProgramme atCentre for quantitative medicineBeth israel deaconess medical centerSingapore eye research instituteMedicine biostatistics health data science programmeMassachusetts institute of technology