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Patient perspectives on informed consent for medical AI: A web-based experiment

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dc.contributor.authorPark, Hai Jin-
dc.date.accessioned2024-11-28T08:27:24Z-
dc.date.available2024-11-28T08:27:24Z-
dc.date.issued2024-01-
dc.identifier.issn2055-2076-
dc.identifier.issn2055-2076-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/195046-
dc.description.abstractObjective: Despite the increasing use of AI applications as a clinical decision support tool in healthcare, patients are often unaware of their use in the physician's decision-making process. This study aims to determine whether doctors should disclose the use of AI tools in diagnosis and what kind of information should be provided. Methods: A survey experiment with 1000 respondents in South Korea was conducted to estimate the patients’ perceived importance of information regarding the use of an AI tool in diagnosis in deciding whether to receive the treatment. Results: The study found that the use of an AI tool increases the perceived importance of information related to its use, compared with when a physician consults with a human radiologist. Information regarding the AI tool when AI is used was perceived by participants either as more important than or similar to the regularly disclosed information regarding short-term effects when AI is not used. Further analysis revealed that gender, age, and income have a statistically significant effect on the perceived importance of every piece of AI information. Conclusions: This study supports the disclosure of AI use in diagnosis during the informed consent process. However, the disclosure should be tailored to the individual patient's needs, as patient preferences for information regarding AI use vary across gender, age and income levels. It is recommended that ethical guidelines be developed for informed consent when using AI in diagnoses that go beyond mere legal requirements.-
dc.format.extent16-
dc.language영어-
dc.language.isoENG-
dc.publisherSAGE Publications-
dc.titlePatient perspectives on informed consent for medical AI: A web-based experiment-
dc.typeArticle-
dc.publisher.location영국-
dc.identifier.doi10.1177/20552076241247938-
dc.identifier.scopusid2-s2.0-85192088362-
dc.identifier.wosid001264017400001-
dc.identifier.bibliographicCitationDigital Health, v.10, pp 1 - 16-
dc.citation.titleDigital Health-
dc.citation.volume10-
dc.citation.startPage1-
dc.citation.endPage16-
dc.type.docTypeArticle-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaHealth Care Sciences & Services-
dc.relation.journalResearchAreaPublic, Environmental & Occupational Health-
dc.relation.journalResearchAreaMedical Informatics-
dc.relation.journalWebOfScienceCategoryHealth Care Sciences & Services-
dc.relation.journalWebOfScienceCategoryHealth Policy & Services-
dc.relation.journalWebOfScienceCategoryPublic, Environmental & Occupational Health-
dc.relation.journalWebOfScienceCategoryMedical Informatics-
dc.subject.keywordPlusARTIFICIAL-INTELLIGENCE-
dc.subject.keywordPlusHEALTH-CARE-
dc.subject.keywordPlusCANCER-
dc.subject.keywordPlusLEGAL-
dc.subject.keywordAuthoralgorithm-
dc.subject.keywordAuthorArtificial intelligence-
dc.subject.keywordAuthorautomation-
dc.subject.keywordAuthordecision support tool for diagnosis-
dc.subject.keywordAuthorduty to disclose-
dc.subject.keywordAuthorinformed consent-
dc.subject.keywordAuthorpatient autonomy-
dc.identifier.urlhttps://journals.sagepub.com/doi/10.1177/20552076241247938-
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