Artificial Intelligence and Machine Learning Model for Healthcare

This study aims to understand the role of artificial intelligence in analyzing and detecting diseases using the electronic healthcare records of a patient. Recently, advances in specialized software, hardware configuration, and applications across a wide range of industries have been made in artificial intelligence (AI) and machine learning. This paper provides an overview of the current developments in AI for biomedical applications. Such as the diagnosis of any disease, living aid, processing of biomedical data, and biomedical research. Consequently, the goal is to examine the value of ML and AI in developing the healthcare domain. Researchers as well as health professionals are paying more attention to artificial intelligence (AI) in the healthcare industry. The data in this research is collected and analyzed using a qualitative technique. Payers, care providers, and life sciences corporations are already using AI in various forms. The objective is to analyze the main application areas; diagnosis and treatment recommendations, patient engagement, adherence, and administrative operations. Findings suggest how AI will improve the quality in the healthcare sector by reducing costs, impacting clinical decision-making, and disease diagnosis. AI and ML models are crucial to the growth of healthcare organizations and healthcare systems. These technologies help identify trends in some disorders, thus significantly impacting healthcare businesses. The study will help us understand how artificial intelligence can be used to improve the patient experience and show that it has the potential to plan and allocate resources in the healthcare sector. Early disease identification is essential for the well-being of a person in the long run. AI and ML also aid in the expansion of the healthcare system.