ArticleFrontiers in endocrinology2025
Personalized cardiometabolic care powered by artificial intelligence.
Article in Frontiers in endocrinology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Advancements in artificial intelligence (AI) are providing a wealth of opportunities for improving clinical practice and healthcare delivery. It is predicted by AI experts that healthcare will change more in the next decade than it has in the previous century due to the volume and speed of these advancing capabilities. In this paper, we will illustrate the potential value of AI by sharing an example of an AI-powered digital health platform, designed to support people living with chronic cardiometabolic conditions and their care teams. The goal is to transform the care continuum from prevention through diagnosis, treatment, and ongoing management, including efficient acute care interventions when needed. The intent is to shift from reactive to proactive care including preventive-based guidance and interventions. AI-powered health technologies enable true person-centered care (i.e., for N=1), but for entire populations at scale (i.e., N >> 1), shifting the traditional mass generalization paradigm to one of mass customization. We demonstrate how an AI-powered digital health platform: 1) supports early detection and diagnosis of chronic conditions such as diabetes and related cardiometabolic conditions with data and insights; 2) optimizes personalized treatment; 3) tracks progress; 4) provides education; and 5) enables longitudinal behavior change to sustain health. We will present current AI capabilities as well as future considerations for the industry. We will also discuss principles that govern the responsible adoption of AI capabilities in healthcare to complement, not replace, the clinician.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.