Emerging Trends in Personalized Medicines Review Article

Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines

  1. Bhupinder Singh Sharda School of Business studies, Sharda University
  2. Ritu Gautam School of Business studies, Sharda University

Abstract

Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse effects. The usage of AI in drug discovery and development identifies potential drug candidates and predicts their efficacy which reduces potential means and costs. One such approach, deep learning, is particularly groundbreaking in genomics, as it unravels intricate genetic data, paves the way for predictive genomics and gene editing, and provides a deeper understanding of disease mechanisms. AI helps in disease prevention and promotion of wellness by enabling early detection, driving lifestyle intervention, and improving mental health care. But we still face challenges related to data privacy, algorithmic bias, and ethics. These are all important issues to consider for ensuring that AI is applied responsibly and equitably in healthcare. Future horizons are promising perhaps real-time monitoring of health continuum, multi-omics data integration, more personalized AI-assisted clinical trials, and ultimately patient empowerment. This shift towards precision medicine through the evolution of AI and deep learning technologies has the potential to revolutionize the way healthcare is delivered and significantly enhance health outcomes and quality of life on a global scale.

Keywords

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