AI in Personalized Medicine: Tailoring Treatment Plans Based on Individual Patient Data

Abstract

The application of AI in personalized medicine is enhancing advanced treatment solutions with respect to every patient’s uniqueness manifested in genetic makeup, life style factors, and clinical background among others. Precision medicine or individualized medicine aims for more effective treatment, fewer side effects of drugs and better utilization of resources in a health care setting. Machine learning (ML) and deep learning (DL) are subsets of AI technologies that assess a tremendous number of factors, including genomics, patients’ EHRs, and lifestyle indicators, to determine which patients will respond better to treatments and which patients are most vulnerable to adverse outcomes. They enhance healthcare practitioners’ ability to provide tailored care to patients to get better results that are less costly in the healthcare system. The purpose of this paper is to review how artificial intelligence will work towards enabling personalized medicine, the issues that exist, and the prospects in the pipeline. Challenges like data privacy, algorithmic bias, and integration into the current healthcare systems are presented, and prospects of the AI –driven personalized medicine in the future improvement of patient care and the development of medical research are examined.