Artificial Intelligence in Personalized Medicine: A Paradigm Shift in Healthcare

Through data-driven insights, AI is redefining personalized medicine by optimizing diagnoses, therapy, and medication discovery. This poll examines how AI, ML, and DL can improve patient outcomes in healthcare. AI-driven algorithms examine genomic, clinical, and biological data to predict illness risks, optimize pharmaceutical efficacy, and adapt treatment regimens. By offering customized healthcare solutions, advanced AI techniques including explainable AI, multi-omics integration, and predictive modeling have greatly improved precision medicine. Wearable technology, real-time monitoring systems, and medical imaging driven by AI all enhance early diagnosis and illness management. Furthermore, AI applications in cardiology, neurology, oncology, and pharmacogenomics show encouraging developments in patient-specific interventions and tailored medications. By offering automated diagnostic support and decision-making tools, AI has the ability to bridge the healthcare accessibility gap, given the doctor-patient ratio of roughly 1:25,000 in rural areas and 1:1456 in metropolitan areas. . Rural doctors, who often lack access to the latest medical best practices, can improve patient care with AI-driven solutions. Despite these benefits, data privacy, morality, model interpretability, and the need for regulatory frameworks to ensure the safe and effective use of AI in medicine remain. The results of numerous investigations are compiled in this survey to demonstrate how AI is revolutionizing healthcare and personalized medicine. The future of healthcare can be redesigned to provide more precise, effective, and patient-centric treatment techniques by tackling current issues and utilizing AI’s capabilities.