AI for Personalized Nutrition and Healthcare Management

Personalised nutrition healthcare sectors are rapidly evolving because of the application of artificial intelligence for designing therapies and nutritional recommendations and plans according to personal needs and genetic profiles. Ai is especially versatile at gathering and sculpting data for various sources, including genetic data, microbiome information and Lifestyle elements. This capability allows an AI-driven platform to generate tolerate dietary advice. [1] In the area of healthcare management, the use of AI in studying EHRs and data from wearable devices to identify diseases at an early stage, risk assessment, and personalised treatment plans. AI is useful in improving precision medicine as well as adjusting a drug prescription map and also transforms the paradigms of remote and Telehealth monitoring due to the ability to assess real-time data and virtual conferences. However, problems like data privacy and security and AI algorithm biases remain challenging. Overcoming these issues is critical to maintaining AI’s effectiveness in these areas in the future. The future trends suggest enhancement of the concept of genomics and enhancement of the AI algorithms, signifying a new era in healthcare for addressing the formidable challenges – better health and value efficacy at a lesser cost. Following this brief introduction to AI and the field’s prospective developments and challenges, this article gets to the underlying focus of exploring the role of AI in personalised nutrition/ dietary therapy/ precision medicine and the prospects of the field. [2]