A Review on Intelligent Health Care System Using Learning Methods Shovon Raul a , Subhasis Das b , Ch.S.V.V.S.N.Murty c , B.S. Kiruthika Devi d* a, b, c Department of Computer Science & Engineering, Aditya College of Engineering and Technology, Surampalem, A.P., India d Research Mentor, CL Educate Ltd., New Delhi *Email: kiruthika.devi@accendere.co.in Abstract: All organizations that are striving for healthy living must establish and maintain updated diet regimens. A health care recommendation system uses data to give medical advice. Machine Learning analyses data to predict future requests and improve healthcare management. An intelligent health care system needs to be built using machine learning and blockchain for health care recommendation systems. This paper discusses in detail the various systems for providing high quality health services. The existing systems that are discussed are Distributed Ledger Technology (DLT), swarm intelligence learning-based systems, adaptive systems, and deep learning systems. Furthermore, various techniques, advantages, disadvantages, tools used, and their accuracy are compared and contrasted. From the studies, it is clear that block chain technology with deep learning techniques provides better accuracy than other conventional methods. Keywords: Block chain, deep learning, healthcare, swarm intelligence, adaptive 1. Introduction Due to the various health hazards in human life after the COVID pandemic, it's becoming essential to have a healthcare management system in human society. It is mandatory to build a personalized diet plan for individuals and to make advanced systems that can be maintained in all organizations working to benefit from a healthy life [1-3]. A healthcare recommendation system is a computer system that can provide a piece of proper medical advice to a person based on specific given data. Our healthcare management system is dependent on the rules and regulations of hospitals and healthcare centers. Machine learning is a subpart of artificial intelligence that comes into play when the data requires classification and predictions for solving user queries [4-9]. The healthcare systems developed based on machine learning models are so complex and dynamic that there is a possibility of leaking vital and sensitive information relative to patients' exposure to data that can lead to severe damage. So, blockchain technology comes into play to reduce security risks as the decentralized approach can preserve the system's trustworthiness. So, a secure distributed machine learning model keeps privacy from being broken and works well [1, 2], [10-13]. __________________________ Corresponding Author, B.S.Kiruthika Devi, Research Mentor, CL Educate Ltd., New Delhi, India; E-mail: kiruthika.devi@accendere.co.in Recent Developments in Electronics and Communication Systems KVS Ramachandra Murthy et al. (Eds.) © 2023 The authors and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0). doi:10.3233/ATDE221251 154