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Use of artificial intelligence to detect correlations between diseases

dc.contributor.authorRomaniuk, О.en
dc.contributor.authorRomaniuk, S.en
dc.contributor.authorPavlov, S.en
dc.contributor.authorTitova, N.en
dc.contributor.authorYaroslavskyi, Ya.en
dc.contributor.authorРоманюк, О. Н.uk
dc.contributor.authorПавлов, С. В.uk
dc.date.accessioned2026-06-08T10:31:56Z
dc.date.available2026-06-08T10:31:56Z
dc.date.issued2026
dc.identifier.citationRomaniuk О., Romaniuk S., Pavlov S., Titova N., Yaroslavskyi Ya. Use of artificial intelligence to detect correlations between diseases // Modern technologies of biomedical engineering = Сучасні технології біомедичної інженерії : proceedings of the 5-th international scientific and technical conference, Оdesа, May 06−08, 2026. Оdesa : Ecologiya, 2026. Р. 151-152.en, uk
dc.identifier.isbn978-617-8420-43-7
dc.identifier.urihttps://ir.lib.vntu.edu.ua//handle/123456789/51746
dc.description.abstractThe features of detecting correlations between diseases using artificial intelligence methods are considered. The possibilities of using machine learning algorithms to process large arrays of medical data and identify hidden dependencies between pathologies are analyzed. The importance of correlation analysis for early diagnosis, risk prediction, and personalization of treatment is substantiated. The main challenges of result interpretation are identified, particularly the distinction between correlation and causation.en
dc.language.isoen_USen_US
dc.publisherOdesa Polytechnic National Universityen
dc.relation.ispartofModern technologies of biomedical engineering = Сучасні технології біомедичної інженерії : proceedings of the 5-th international scientific and technical conference, Оdesа, May 06−08, 2026 : 151-152.en, uk
dc.subjectartificial intelligenceen
dc.subjectmachine learningen
dc.subjectcorrelation analysisen
dc.subjectmedical dataen
dc.subjectdiseasesen
dc.subjectdiagnosticsen
dc.subjectforecastingen
dc.titleUse of artificial intelligence to detect correlations between diseasesen
dc.typeThesis
dc.identifier.udc615.47:616-89


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