THE ROLE OF ARTIFICIAL INTELLIGENCE IN PREDICTIVE HEALTHCARE: TRANSFORMING EARLY DIAGNOSIS AND PREVENTIVE MEDICINE

AI technology is a complex and developing area that has become a promising platform for predicting and preventing diseases. The purpose of this study was the improvement achieved through AI models like Random Forest and CNNs (Convolutional Neural Network) when compared with traditional diagnostic techniques in terms of accuracy, sensitivity, and specificity. The study showed that AI models had superior results to the classical ones, and CNNs had the best metrics; these models can analyze big data and study early signs of diseases. The results of this research have highlighted the capability of artificial intelligence to drive shocking changes in this essential sector of our lives through timely interferences and personalized treatment plans that will in one way or another enhance the quality of a patient’s life or a family’s budget towards treating diseases. The data quality, algorithm interpretability, and ethical issues are the issues that have not been solved completely yet. They are important to fix and address so that the use of AI to be fair and effectively applied to clinical practice. The study especially stresses on multi-disciplinary approach with technologists, clinicians, and policymakers to provide ethical and efficient solutions to integrating AI innovations in healthcare. It should be directed towards the creation of post-hoc interpretable models, as well as the construction of appropriate legal instruments to encourage the practice of AI in medical practice. The revolutionary application of AI in the prognostication of health and its capability to completely reframe early identification and preventive measures.