Optimized Predictive Models in Health Care Using Machine Learning

4Analysis of Smart Technologies in Healthcare

Shikha Jain^1,2*, Navneet Kaur³, Manisha Malhotra³ and Manjot Kaur⁴

¹University Institute of Computing, Chandigarh University, Mohali, India

²Department of Computer Science, Kirori Mal College, University of Delhi, Delhi, India

³Department of Computer Science and Engineering, Chandigarh University, Mohali, India

⁴Fidelity Information Services Ltd, Mohali, India

Abstract

Emerging fields, such as machine learning, deep learning, blockchain, and Internet of Things, have greatly benefited the healthcare industry. These technologies have shifted the healthcare paradigm by developing various ML models that aid in recognizing and understanding image patterns, providing medical decision support, and maintaining and digitizing patients’ electronic health records. Their ability to aid decision making, optimize workflows, and free up valuable human time is transforming how people deliver and receive care. This saves time for doctors and other medical authorities because they accept preliminary information about the patient via digital systems. Motivated by this thought, this chapter aims to investigate and analyze these cutting-edge technologies, like blockchain, the Internet of Things, machine learning, deep learning, etc., used in healthcare systems. We also make recommendations for future applications while briefly discussing the risks and difficulties associated with various healthcare applications, such as system privacy and security, ...