Does improving diagnostic accuracy increase artificial intelligence adoption? A public acceptance survey using randomized scenarios of diagnostic methods

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October 18, 2024

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http://creativecommons.org/licenses/by-nc-nd/ , info:eu-repo/semantics/OpenAccess




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Yulin Hswen et al., « Does improving diagnostic accuracy increase artificial intelligence adoption? A public acceptance survey using randomized scenarios of diagnostic methods », HALSHS : archive ouverte en Sciences de l’Homme et de la Société, ID : 10.36922/aih.3561


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This study examines the acceptance of artificial intelligence (AI)-based diagnostic alternatives compared to traditional biological testing through a randomized scenario experiment in the domain of neurodegenerative diseases (NDs). A total of 3225 pairwise choices of ND risk-prediction tools were offered to participants, with 1482 choices comparing AI with the biological saliva test and 1743 comparing AI+ with the saliva test (with AI+ using digital consumer data, in addition to electronic medical data). Overall, only 36.68% of responses showed preferences for AI/AI+ alternatives. Stratified by AI sensitivity levels, acceptance rates for AI/AI+ were 35.04% at 60% sensitivity and 31.63% at 70% sensitivity, and increased markedly to 48.68% at 95% sensitivity (p

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