Anita Shinde and Dipti D Patil*

¹Research Scholar, SKNCOE research centre, Savitribai Phule Pune University, Pune, India
²Department of Information Technology. MKSSS’s Cummins College of Engineering for Women, Pune, India

*Corresponding Author: Dipti D Patil, Department of Information Technology. MKSSS’s Cummins College of Engineering for Women, Pune, India.

Received: October 21, 2021; Published: March 03, 2022

Abstract

Large amount of clinical data spread across various sites on the Internet obstructs users from extracting useful information which can be used for enhancing the healthy life style. Similarly, overload of medical information (e.g. medicines prescriptions, test reports, treatment) has created many problems to medical professionals in building patient oriented decisions. To overcome information overload issue on Internet, Recommendation System has been developed in various fields as a competent tool. There is need to incorporate recommender system in healthcare domain which will be helpful to end-users (patients) and medical professionals in making précised and efficient health related decisions. Now days, the application of recommender system for healthcare has become a critical research topic because of its remarkable benefits in generating relevant personalized recommendations and assisting patients in taking correct health related decisions. In this article, we discuss overview of existing research on recommender systems in healthcare domain. A general idea about three recommendation techniques such as content-based, collaborative filtering (CF)-based, and hybrid methods is explained in context of healthcare domain. Examples of various recommender systems include as food/diet recommendation, drug recommendation, lifestyle recommendation, and healthcare professional recommendation. Finally the research issues need to be addressed are listed.

Keywords: Recommender Systems; Healthcare; Collaborative Filtering; Similarity Measures; Big Data; User Ratings; Decision Support System