ArticleNEJM AI2025
AI-Powered Diabetes Precision Health: From Data to Action.
Article in NEJM AI, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Diabetes has become a major public health challenge due to its high prevalence and chronic nature, with many individuals managing the condition for decades. The vast heterogeneity in diabetes necessitates personalized approaches to its prevention, diagnosis, treatment, and prognosis. Recently, the National Institute of Diabetes and Digestive and Kidney Diseases at the National Institutes of Health convened experts from the fields of diabetes and AI to identify and discuss existing gaps, as well as potentially transformative opportunities and actionable items enabled by recent advancements in AI. One prominent theme that has emerged from this discussion was the considerable potential of AI in Diabetes Precision Health, a field that warrants greater attention. The purpose of this article is to describe the opportunities and challenges identified during the workshop and outline potential strategies recommended by workshop attendees to advance this promising field.
Identifiers
What OpenQuestion holds
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.