Leveraging Generative AI and Advanced Predictive Models to Redefine Personalized Medicine and Patient-Centered Care in Modern Healthcare Systems

Abstract

Unprecedented scientific and technological advancements are revolutionizing medicine and healthcare, yielding tremendous improvements in healthcare quality, well-being, and longevity. Digital health technologies are central to this transformative development; they are set to revolutionize all aspects of healthcare, healthcare delivery, and health management. For example, generative artificial intelligence (AI) has already demonstrated unprecedented, transformative impact on healthcare and patient outcomes. In recent years, generative AI and advanced predictive models have astonishingly innovated patients’ therapeutic courses, diagnostic journeys, and care provisioning modalities, fundamentally and inapprehensible altering their patient experiences. Prudent and ethical uses of such transformative generative AI and advanced predictive models will therefore be crucial for ensuring not only their utility and safety, but more importantly the quality and sustainability of these transformative patient experiences. Broadly tailored health solutions and services motivated by the profit-driven healthcare models are likely not conducive to long-term patient outcomes and well-being. Adaptive healthcare solutions catering to specific, individual, and personalized patient, potentially beyond biomedicine, will be pivotal in ensuring patient health and sustainability. A well-informed, empowering patient will be a crucial is appearing for ensuring that these widely transformative technologies will be used for the patient centricity. There is an urgent need to increase awareness and understanding of patients, patient communities, and healthcare providers of such transformative AI tools. In this regard, generative AI, with their unique capabilities of generating multi-modal and multi-disciplinary outputs, can play a transformative role in the trustworthy, intelligible summarization of the vast and exponentially growing body of pivotal emergent evidence accumulated in this field. ITERATIVE, EVIDENCE-DRIVEN AI-HUMAN GUIDED SYNTHESIS LOOPS. The generative AI can align the automatically generated summaries with the guidance and assistance from healthcare professionals, ensuring that all necessary caveats, considerations and potential conflicts with the emerging evidence are adequately considered and communicated to end-users. The informal treatment and consideration of the summarization output derived from the generative AI by professional healthcare providers will enable the generative AI to better understand the underlying queries, requirements, and expectations and by effecting concinnity, develop more efficaciously and pertinently tailored summarization output.