The Future of Healthcare: A Machine Learning Revolution
Data collection issues, ML model selection, and the varied uses of ML, from personalized treatment plans to disease detection, are discussed in this paper, which aims to create futuristic healthcare systems which are more efficient and focused on patient care.
Abstract
The healthcare sector is undergoing a profound transformation driven by technological advancements, prominently featuring the integration of machine learning into its framework. This paper explores the various uses, advantages, disadvantages, and ethical concerns related to machine learning in healthcare. Data collection issues, ML model selection, and the varied uses of ML, from personalized treatment plans to disease detection, are discussed in this paper. This paper also discusses issues related to data security and privacy, as well as the effects of ML on healthcare efficiency and patient outcomes. Also covered are potential future developments and new technology that might alter the healthcare system. The research intends to analyze these essential features of machine learning in healthcare so that healthcare organizations can better understand its transformational potential and the obstacles that come with it. The goal is to create futuristic healthcare systems which are more efficient and focused on patient care.