AI's Role in Personalized Medication Management

Abstract

Healthcare has gone through a paradigm change, specifically in personalized medicine, due to the development of Artificial Intelligence (AI) technology. This chapter will discuss how AI is transforming healthcare delivery in general, particularly through precision medicine. Such AI technologies such as machine learning, deep learning, natural language processing, predictive analytics, robotics, and automation can utilize extensive databases that include patient genomics, medical history and realtime health monitoring, as well as patient demographics. By using AI to integrate data from Electronic Health records along with other patient sources, genomic data, and wearable IoT devices, it provides a holistic profiling of patients to predict their responses to drugs and identify possible adverse effects. Besides, AI also fast tracks drug discovery and development by target identification to drug repurposing, reducing time frames for research and development. Advances in Clinical Decision Support Systems (CDSS) enhance the decision-making process, providing real-time insights that guide healthcare professionals. However, the implementation of AI in personalized medicine comes with its own set of challenges. However, there are ethical issues associated with data privacy, biases in AI algorithms, regulatory considerations, and more. When it comes to the adoption of AI, the integration with existing infrastructure, training, and educating health professionals become key elements. There is a lot of potential for the future, as technology is constantly advancing and is sure to remove barriers preventing us from a more efficient, patient-centered, healthcare model.

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