A Study of Health Recommender Systems: Analyzing the Advancement of Sustainable Health Recommender Systems Using NLP Techniques

Over the years, amount of healthcare data has immensely increased due to technological development. Although it provided user with ease access, large amounts can be challenging information overload. In case domain, any misinterpreted may cause a severe situation. Recommender systems are proving beneficial their use in extracting required quickly. this paper, we conducted an analysis existing health recommender using NLP techniques. We reviewed solutions for systems, described and compared them based on features algorithms employed, presented future research directions. Our findings indicate that popular applications developed patient-doctor match, recommending drugs, cancer predictions, chronic disease diagnosis, patients heart problems. Further, given knowledge sustainable products, system suggest products these characteristics.