Author: Om Prakash Sharma
Abstract: Artificial Intelligence (AI) has emerged as a transformative force in healthcare, particularly in medical diagnosis systems. AI-based diagnostic tools leverage machine learning algorithms, deep learning models, and natural language processing to support clinicians in detecting diseases, predicting outcomes, and recommending treatments. This review explores the current state of AI-based medical diagnosis systems, their architectures, applications, benefits, challenges, and ethical considerations. Emphasis is placed on AI models used in radiology, pathology, cardiology, and general clinical decision-making. The paper also highlights the role of big data and Internet of Things (IoT) integration in enhancing diagnostic accuracy. While AI offers significant improvements in efficiency, accuracy, and cost reduction, challenges such as data privacy, algorithmic bias, and regulatory compliance remain critical. This study aims to provide a comprehensive understanding of AI-based diagnostic systems, their practical applications, and future research directions.
Keywords: Artificial Intelligence, Medical Diagnosis, Machine Learning, Deep Learning, Clinical Decision Support, Healthcare Technology, Big Data, IoT.
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