Use of AI in Early Disease Detection

Abstract

Artificial Intelligence (AI) has emerged as a valuable technology in health care primarily for the early detection and prediction of diseases. AI leverages machine learning and deep learning systems to analyse complex and large healthcare datasets to identify disease related patterns and abnormalities that may not be easily detected using conventional methods. This review discusses the advancement and role of AI in early disease detection and its applications in various aspects of healthcare. This review further explores the methodology involved in developing AI-based detection systems focusing mainly on data collection, model training, optimisation, and model validation. Various applications and potential advantages of AI, including improved diagnostic accuracy, early identification of disease, along with their role in assisting clinical decision making is discussed. However, challenges such as data quality and availability, privacy concerns, regulatory issues may affect the implementation of AI in healthcare. Finally, regulatory and ethical considerations, following future directions including explainable AI, personalised medicine, wearable devices are explored in this review. Overall, AI shows considerable promise for early disease detection, but its successful integration requires reliable data, proper validation, responsible regulations, and human-AI collaboration.