Recommender system for health care analysis using machine learning technique: a review

Salim G. Shaikh, B. Suresh Kumar, Geetika Narang
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引用次数: 4

Abstract

Abstract 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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基于机器学习技术的医疗保健分析推荐系统综述
摘要推荐系统使用不同的机器学习(ML)技术来推荐用户,并在各种应用领域推荐服务或实体,例如在医疗保健推荐系统(HRS)中。由于文献中显示了大量的算法,HRS和各个应用部门现在都在利用人工智能领域的ML算法。然而,在健康推荐系统的情况下,选择合适的ML算法似乎是一项耗时的任务。然而,推荐系统在不同服务领域的发展面临着算法选择以提高准确性的问题。本文通过对文献的调查,研究了ML技术在健康应用推荐系统中的应用。本文的目的是(i)认识到使用ML和深度学习算法的推荐系统在健康应用中的文献综述发现。(ii)借助以往研究中的差距,协助新的研究人员。本研究的结果是利用ML技术的混合方法,提出了一种新的推荐系统在蚊媒疾病健康应用中的应用。
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CiteScore
4.10
自引率
6.20%
发文量
38
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