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| Élément Dublin Core | Valeur | Langue |
|---|---|---|
| dc.contributor.author | BARIK, Mohamed | - |
| dc.contributor.author | LASFER, Yaaqoub | - |
| dc.date.accessioned | 2025-11-23T08:45:15Z | - |
| dc.date.available | 2025-11-23T08:45:15Z | - |
| dc.date.issued | 2025-06-16 | - |
| dc.identifier.uri | http://dspace.univ-tiaret.dz:80/handle/123456789/16883 | - |
| dc.description.abstract | The 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 Filtering | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | University of Ibn Khaldoun Tiaret | en_US |
| dc.subject | Recommender System | en_US |
| dc.subject | Healthcare | en_US |
| dc.subject | Drug Recommendation System | en_US |
| dc.subject | Neural Collaborative Filtering, | en_US |
| dc.title | Developing a Drug Recommendation System: Design, Implementation and Evaluation | en_US |
| dc.type | Thesis | en_US |
| Collection(s) : | Master | |
Fichier(s) constituant ce document :
| Fichier | Description | Taille | Format | |
|---|---|---|---|---|
| TH.M.INF.2025.28.pdf | 8,45 MB | Adobe PDF | Voir/Ouvrir |
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