Fusion of Machine Learning and Blockchain Techniques in IoT-based Smart Healthcare Systems

Abstract

Smart healthcare is one of the rising areas of research in collaboration with smart techniques like sensors, the Internet of Things (IoT), and various information analytics techniques to convey effective healthcare services to the patients at a lesser amount of cost. The healthcare system faces lots of problems in dealing with a large volume of data generated day by day, and processing and exploring useful information from it. Such a large volume of data is generated through various IoT-based medical gadgets, electronic health records, wearable sensors, telemedicine, and mobile health services that may demand effective, fast, and secure data analysis techniques to offer high-quality services to patients. To provide such types of services, machine learning and blockchain techniques are highly appreciated in various domains. This study mainly discusses the categorization of powerful machine learning and blockchain techniques highly effective to process such a vast amount of data. As the healthcare system encompasses highly sensitive data regarding patient health as well as personal information which must require appropriate security services, blockchain technology can be used as an effective solution for offering security services to highly sensitive data. Machine learning 246and blockchain technology together provide lots of opportunities for the healthcare system to attain all its goals like reduced healthcare cost, effective diagnosis, timely treatment, offering transparency in regulatory reporting, and effective health data management. The main aim of this chapter is to provide a detailed description of the relationship between blockchain and machine learning techniques to empower an IoT-based healthcare system. Along with that, this chapter also discusses the major issues and challenges faced while implementing IoT-based smart healthcare systems by collaborating machine learning and blockchain techniques.