Machine Learning Approaches for Convergence of IoT and Blockchain

6Machine Learning Applications for IoT Healthcare

Neha Agarwal¹, Pushpa Singh^2*, Narendra Singh³, Krishna Kant Singh⁴ and Rohit Jain⁵

¹Dept. of Computer Science & Engineering, Amity University, Noida, Uttar Pradesh, India

²Dept. of Computer Science and Engineering, Delhi Technical Campus, Greater Noida, Uttar Pradesh, India

³Dept. of Management Studies, GL Bajaj Institute of Management & Research, Greater Noida, India

⁴Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India

⁵Dept. of Computer Science & Engineering, Penn State University, United States

Abstract

Healthcare sectors are gradually accepting technology that provides various remote healthcare facility, disease prediction, and in-home diagnostics capabilities, which combine Machine Learning (ML) and the Internet of Things (IoT). ML offers tools for management of electronic records, integration of data, and techniques for computer-aided diagnosis which helps in disease diagnosis, prediction, and treatment suggestion. The IoT connect all type medical devices, patients monitoring tools, and wearable devices that can send immediate data to concern authority like doctor. In this chapter, authors focus on ML applications for IoT-based healthcare. In this chapter, first, we introduce the basic concepts of ML and IoT and summarize the advantages of the techniques over traditional approaches of healthcare. We described the challenges of using ML and IoT in research and finally presented applications ...