Interpretable deep learning method for medical image diagnosis

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dc.contributor.authorManziuk, Eduard
dc.contributor.authorBarmak, Oleksandr
dc.contributor.authorKrak, Iurii
dc.contributor.authorPetliak, N.
dc.contributor.authorJin, Zh.
dc.contributor.authorRadiuk, Pavlo
dc.date.accessioned2024-11-26T12:42:40Z
dc.date.available2024-11-26T12:42:40Z
dc.date.issued2024-06-23
dc.description.abstractIncorporating artificial intelligence into the medical field holds immense potential, but it also raises significant challenges that must be addressed to ensure patient safety and ethical practices. While AI can enhance efficiency and support decision-making processes, its application in healthcare demands utmost caution and rigorous safeguards.
dc.identifier.citationManziuk E., Barmak O., Krak I.2,3, Petliak N., Jin Zh., Radiuk P. Interpretable deep learning method for medical image diagnosis // Intelligent Systems Of Decision-Making And Problems Of Computational Intelligence (ISDMCI’2024) : Conference proceedings, Khmelnytskyi, Ukraine; Usti nad Labem, Czech Republic, 20–23 June 2024 / ed. by V. Lytvynenko, S. Babichev. Kherson, 2024. P. 26–28. URL: https://www.isdmci.ks.ua/
dc.identifier.isbn978-617-8187-21-7
dc.identifier.urihttps://elar.khmnu.edu.ua/handle/123456789/17117
dc.language.isoen
dc.publisherФОП Вишемирський В.С.
dc.subjectInterpretable deep learning
dc.subjectMedical image diagnosis
dc.subjectExplainable artificial intelligence (XAI)
dc.subject.udc004.89
dc.titleInterpretable deep learning method for medical image diagnosis
dc.typeТези доповідей
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