AI Driven Predictive Model for Tailored Treatment Plan

Personalized medicine in healthcare has emerged as a promising approach to closing the gap in patient outcomes. Leveraging artificial intelligence (AI) technology, particularly predictive models, offers a way to customize treatments based on patient characteristics, thus optimizing treatment for health and reducing adverse effects. This article provides a comprehensive review of existing intelligence based predictive models in healthcare, focusing on their application in clinical strategies. Different methods, data sets and results were used in this study. Develops research studies and highlights strengths, limitations, and potential ways to develop AI driven predictive models to aid clinical practice. It also explores the ethical and practical implications of using such models in the clinical setting, including data privacy, algorithmic bias, and governance issues. This study contributes to the ongoing debate about the potential replacement of cognitive skills in healthcare by providing a critical review of current methods and suggesting paths forward for research and future use. By leveraging the power of AI- powered predictive models, doctors can move closer to personalized medicine, ultimately improving patient outcomes and enhancing the quality of care.