Machine Learning Method to Identifying Early Factors Leading to Burnout Among Medical Professionals

dc.contributor.authorPerova, Iryna
dc.contributor.authorZavgorodnii, Igor
dc.contributor.authorЗавгородній, Ігор Володимирович
dc.contributor.authorLitovchenko, Olena
dc.contributor.authorЛітовченко, Олена Леонідівна
dc.contributor.authorBoeckelmann, Irina
dc.contributor.authorChehovska, Iryna
dc.contributor.authorЧеховська, Іриан Миколаївна
dc.contributor.authorChyhryn, Danylo
dc.contributor.authorNovytskyy, Oleksandr
dc.date.accessioned2025-02-25T13:16:25Z
dc.date.issued2024
dc.identifier.citationMachine Learning Method to Identifying Early Factors Leading to Burnout Among Medical Professionals / I. Perova, I. Zavgorodnii, O. Litovchenko, I. Boeckelmann, I. Chehovska, D. Chyhryn, O. Novytskyy // Lecture Notes in Data Engineering, Computational Intelligence, and Decision-Making : International Scientific Conference “Intelligent Systems of Decision-Making and Problems of Computational Intelligence”, Proceedings / S. Babichev, V. Lytvynenko. – [S. l. : s. n.], 2024. – Volume 1. – Р. 287–307.
dc.identifier.urihttps://repo.knmu.edu.ua/handle/123456789/35788
dc.language.isoen
dc.subject2025а/2024
dc.titleMachine Learning Method to Identifying Early Factors Leading to Burnout Among Medical Professionals
dc.typeArticle

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