Advancing competitive position in healthcare: a hybrid metaheuristic nutrition decision support system

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dc.contributor.authorIleri, Yusuf Yalcin
dc.contributor.authorHacibeyoglu, Mehmet
dc.date.accessioned2024-02-23T13:59:59Z
dc.date.available2024-02-23T13:59:59Z
dc.date.issued2019
dc.departmentNEÜen_US
dc.description.abstractIn the highly competitive environment of healthcare industry, managers incorporate patient centered care as a major component in the healthcare mission. Management information systems have gained increasing attention to develop effective plans for patient centered care, and quality improvement in healthcare organizations. Consumers are becoming actively involved in their health, which is great for patient engagement, but to meet this demand, healthcare providers need to make significant changes. Information technology and artificial intelligence can significantly improve workflows for healthcare professionals, and support the development of new services to meet changing consumer demands while maintaining costs. In this study, we aimed to build a decision support system including Genetic algorithm and Simulated Annealing metaheuristic machine learning methods for nutritionists to regulate a hospitals' nutrition cycle and provide the best possible diet menu solutions while decreasing costs. Our main reason of using hybrid metaheuristic machine learning methods is to obtain a better quality solution on the problem dealt with study. Experimental results showed that; the proposed system is a novel, smart, cost-effective, flexible and machine learning based decision support system for nutritionist and healthcare managers.en_US
dc.identifier.doi10.1007/s13042-018-0820-y
dc.identifier.endpage1398en_US
dc.identifier.issn1868-8071
dc.identifier.issn1868-808X
dc.identifier.issue6en_US
dc.identifier.scopus2-s2.0-85066112098en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage1385en_US
dc.identifier.urihttps://doi.org/10.1007/s13042-018-0820-y
dc.identifier.urihttps://hdl.handle.net/20.500.12452/11406
dc.identifier.volume10en_US
dc.identifier.wosWOS:000468920300012en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Heidelbergen_US
dc.relation.ispartofInternational Journal Of Machine Learning And Cyberneticsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectGenetic Algorithmen_US
dc.subjectHospital Information Management Systemen_US
dc.subjectNutrition Decision Support Systemen_US
dc.subjectOptimization Problemen_US
dc.subjectSimulated Annealingen_US
dc.titleAdvancing competitive position in healthcare: a hybrid metaheuristic nutrition decision support systemen_US
dc.typeArticleen_US

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