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المؤلفKhalid, Nazish
المؤلفQayyum, Adnan
المؤلفBilal, Muhammad
المؤلفAl-Fuqaha, Ala
المؤلفQadir, Junaid
تاريخ الإتاحة2023-07-13T05:40:51Z
تاريخ النشر2023
اسم المنشورComputers in Biology and Medicine
المصدرScopus
الرقم المعياري الدولي للكتاب104825
معرّف المصادر الموحدhttp://dx.doi.org/10.1016/j.compbiomed.2023.106848
معرّف المصادر الموحدhttp://hdl.handle.net/10576/45567
الملخصThere has been an increasing interest in translating artificial intelligence (AI) research into clinically-validated applications to improve the performance, capacity, and efficacy of healthcare services. Despite substantial research worldwide, very few AI-based applications have successfully made it to clinics. Key barriers to the widespread adoption of clinically validated AI applications include non-standardized medical records, limited availability of curated datasets, and stringent legal/ethical requirements to preserve patients' privacy. Therefore, there is a pressing need to improvise new data-sharing methods in the age of AI that preserve patient privacy while developing AI-based healthcare applications. In the literature, significant attention has been devoted to developing privacy-preserving techniques and overcoming the issues hampering AI adoption in an actual clinical environment. To this end, this study summarizes the state-of-the-art approaches for preserving privacy in AI-based healthcare applications. Prominent privacy-preserving techniques such as Federated Learning and Hybrid Techniques are elaborated along with potential privacy attacks, security challenges, and future directions. 2023 The Author(s)
راعي المشروعThis publication was made possible by NPRP grant # 13S-0206-200273 from the Qatar National Research Fund (a member of the Qatar Foundation). Open Access funding provided by the Qatar National Library. The statements made herein are solely the responsibility of the authors.
اللغةen
الناشرElsevier
الموضوعArtificial intelligence (AI)
Electronic health record (EHR)
Privacy
Privacy preservation
العنوانPrivacy-preserving artificial intelligence in healthcare: Techniques and applications
النوعArticle Review
رقم المجلد158
dc.accessType Open Access


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