Recommender system for health care analysis using machine learning technique: a review.
Recommender systems use different techniques of machine learning (ML) to suggest users and recommend service or entity in various field of application such as in health care recommender system (HRS). Due to the vast count of algorithms shown in the literature, HRS and various application sectors are...
| Publicado en: | Theoretical Issues in Ergonomics Science Vol. 23; no. 5; pp. 613 - 643 |
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| Autores principales: | , , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Taylor & Francis Ltd
Sep2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| Sumario: | Recommender systems use different techniques of machine learning (ML) to suggest users and recommend service or entity in various field of application such as in health care recommender system (HRS). Due to the vast count of algorithms shown in the literature, HRS and various application sectors are now utilizing ML algorithms from the area of artificial intelligence. However, selecting an appropriate ML algorithm in the case of a health recommender system seems to be a time-consuming task. However the development of recommender system in different service domain faces problems of algorithms selection for better accuracy. This article examined the usage of ML techniques in recommender systems for health applications through a survey of the literature. The objectives of this article are (i) recognize the literature review finding of recommender system in health applications using ML and deep learning algorithms. (ii) Assist new researchers with the help of gap in previous research. The results of this study is to proposed new recommender system in health application of mosquito borne disease by using hybrid approach of ML technique. |
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