Artificial Intelligence Revolution in Healthcare: From Patient Care to Disease Diagnosis

Abstract

Artificial intelligence (AI) innovation has had a profound effect on the current healthcare industry, delivering a broad range of approaches from machine learning to deep learning. Numerous elements of healthcare, like as illness diagnosis, medication research, and patient risk assessment find widespread use for these AI approaches. AI has become a ground-breaking technology with enormous promise in the medical industry. AI plays a crucial role in aiding medical practitioners with illness diagnosis, therapy selection, and patient monitoring by using machine learning (ML) and deep learning (DL), eventually improving the accuracy and efficacy of healthcare services. A smoother healthcare continuum is also made possible by AI, which has sped up the process of moving patients from hospitals to their homes for rehabilitation. This paper offers a thorough analysis of AI methods used to diagnose a variety of illnesses, such as Alzheimer’s disease, diabetes, TB, hypertension, and liver conditions. It includes studies that integrate feature extraction and classification methods with medical imaging datasets, such as Kaggle for prediction purposes. The use of AI in healthcare has the potential to significantly improve patient care standards, illness diagnostic processes, and overall healthcare system effectiveness. This opens the door for a collaborative synergy between AI and medical specialists, allowing them to cooperate more successfully in promoting healthcare and ultimately enhancing the well-being of patients.