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dc.contributor.authorBARIK, Mohamed-
dc.contributor.authorLASFER, Yaaqoub-
dc.date.accessioned2025-11-23T08:45:15Z-
dc.date.available2025-11-23T08:45:15Z-
dc.date.issued2025-06-16-
dc.identifier.urihttp://dspace.univ-tiaret.dz:80/handle/123456789/16883-
dc.description.abstractThe choice of the right drug remains a complex decision for physicians,despite floods of patient data and continuously growing drug lists.We see recommendation systems helping in many online spaces.But when it comes to health,especially drug choices,these systems need to be much alert.Many current drug recommendation systems face problems and challenges.This turns their suggestions to be not precise or clinically helpful as they could be. This research addresses precisely these issues,by building a new kind of drug recommendation system, rooted in dee learning.By adopting the highly regarded Neural Collaborative Filteringen_US
dc.language.isoenen_US
dc.publisherUniversity of Ibn Khaldoun Tiareten_US
dc.subjectRecommender Systemen_US
dc.subjectHealthcareen_US
dc.subjectDrug Recommendation Systemen_US
dc.subjectNeural Collaborative Filtering,en_US
dc.titleDeveloping a Drug Recommendation System: Design, Implementation and Evaluationen_US
dc.typeThesisen_US
Collection(s) :Master

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