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Predictive Analytics in Personalized Medical Care: Early Risk Assessment and Management
Abstract
The widespread implementation and utilization of electronic health records has resulted in technological advancements in computers and data, which have enabled the creation of patient care models that are automated, personalized, and instantaneous. Artificial intelligence (AI), machine learning (ML), reinforcement learning (RL), and deep learning, are well adapted to use such data. This chapter examines how AI-driven solutions can revolutionize the healthcare industry, with emphasis on how ML techniques can be used to provide personalized medical interventions. The chapter covers ethical frameworks that must be in place in order to guarantee the proper application of AI-driven medical solutions. The chapter also addresses issues with data privacy, algorithm bias, and integration difficulties with current healthcare infrastructures. In order to fully utilize ML while maintaining patient safety, privacy, and equity in the delivery of healthcare, it highlights the significance of cooperative efforts between healthcare practitioners, technology specialists, legislators, and ethicists.
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