博碩士論文 111421027 完整後設資料紀錄

DC 欄位 語言
DC.contributor企業管理學系zh_TW
DC.creator張琤華zh_TW
DC.creatorCheng-Hua Changen_US
dc.date.accessioned2024-7-10T07:39:07Z
dc.date.available2024-7-10T07:39:07Z
dc.date.issued2024
dc.identifier.urihttp://ir.lib.ncu.edu.tw:444/thesis/view_etd.asp?URN=111421027
dc.contributor.department企業管理學系zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract現今醫療體系已面臨人力不足與城鄉差距等問題,在AI浪潮之下,許多相關應用已實 施在臨床體系下,然而大部分的醫護人員與病患對於醫療AI的應用持抗拒態度。本研 究針對一般民眾、醫護人員、AI領域人員,在不同疾病風險下進行變數操縱,如AI解 釋性、Simon的有限理性,討論人類對於醫療AI應用態度之影響。此外,與先前研究較 為不同的是本研究清楚界定人類對於信任AI能力與是否接納AI診斷之差別。最後,本 研究成功操作AI解釋性之變數,並證實風險的調節效果,為未來醫療AI臨床應用打下 良好基石。zh_TW
dc.description.abstractThe current healthcare system faces issues such as workforce shortages and urban-rural disparities. Amid the AI wave, many related applications have already been implemented in clinical systems. However, most healthcare professionals and patients resist the application of medical AI. This study investigates the attitudes toward medical AI applications among the general public, healthcare professionals, and AI specialists, by manipulating variables such as AI explainability and Simon′s bounded rationality under different disease risk. Additionally, unlike previous studies, this research clearly differentiates between trust in AI capabilities and acceptance of AI diagnoses. Finally, this study successfully manipulates the variable of AI explainability and confirms the moderating effect of risk, laying a solid foundation for future clinical applications of medical AI.en_US
DC.subject人工智慧zh_TW
DC.subject醫療AIzh_TW
DC.subjectAI解釋性zh_TW
DC.subject有限理性zh_TW
DC.subject風險zh_TW
DC.subjectArtificial Intelligenceen_US
DC.subjectMedical AIen_US
DC.subjectAI explainabilityen_US
DC.subjectbounded rationalityen_US
DC.subjectrisken_US
DC.title人類醫生或AI醫生?—人工智能醫療診斷應用之研究zh_TW
dc.language.isozh-TWzh-TW
DC.titleHuman Doctors vs. AI Doctors: A Study on the Application of AI in Medical Diagnosisen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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