Leveraging Artificial Intelligence for Predictive Models in Personalized Healthcare

Abstract

Emerging as a transforming tool in personalized healthcare, artificial intelligence (AI) provides predictive modeling features that improve patient management, disease diagnosis, and treatment planning. With an emphasis on machine learning (ML) and deep learning (DL) approaches to examine patient data, identify trends, and estimate health outcomes, this paper investigates the integration of AI-driven predictive models in personalised healthcare AI helps early illness diagnosis, risk assessment, and customized therapy recommendations by using big-scale medical information, so enhancing clinical decision-making and patient outcomes. To develop dynamic, patient-specific healthcare plans, the research also emphasizes the part artificial intelligence (AI) plays in genetics, wearable technology, and electronic health records (EHRs). The paper also looks at the difficulties in adopting artificial intelligence including ethical issues, data privacy issues, model interpretability, and regulatory compliance need. Notwithstanding these obstacles, by enabling healthcare to be more proactive, efficient, and patient-centered, AI-driven prediction models have great power to transform individualized treatment. This work offers analysis of the most recent developments in artificial intelligence-powered prediction modeling and future perspectives for including AI into systems of precision medicine. The results highlight the need of strong artificial intelligence systems guaranteeing accuracy, openness, and ethical application in clinical practice.