Evidence map›Paper›PMID 41959775›Full record

ArticlemedRxiv : the preprint server for health sciences2026

A Manual of Procedures for the Generation of the AI-Ready and Exploratory Atlas for Diabetes Insights (AI-READI) Database.

Dawn S Matthies, Jeffrey C Edberg, Sally L Baxter, Aaron Y Lee, Cecilia S Lee, Gerald McGwin, Julia P Owen, Linda M Zangwill, Cynthia Owsley

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Dawn S MatthiesDepartment of Ophthalmology & Visual Sciences, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL.ORCID 0000-0003-4008-7182
Jeffrey C EdbergDepartment of Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham AL.ORCID 0000-0002-0248-7647
Sally L BaxterDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0002-5271-7690
Aaron Y LeeJohn F. Hardesty MD Department of Ophthalmology and Visual Sciences, Washington University, St. Louis, MO.ORCID 0000-0002-7452-1648
Cecilia S LeeJohn F. Hardesty MD Department of Ophthalmology and Visual Sciences, Washington University, St. Louis, MO.ORCID 0000-0003-1994-7213
Gerald McGwinDepartment of Ophthalmology & Visual Sciences, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL.ORCID 0000-0001-9592-1133
Julia P OwenJohn F. Hardesty MD Department of Ophthalmology and Visual Sciences, Washington University, St. Louis, MO.ORCID 0000-0003-4137-3834
Linda M ZangwillDivision of Ophthalmology Informatics and Data Science, Hamilton Glaucoma Center, Viterbi Family Department of Ophthalmology and Shiley Eye Institute, University of California, San Diego, La Jolla, CA, USA.ORCID 0000-0002-1143-5224
Cynthia OwsleyDepartment of Ophthalmology & Visual Sciences, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, AL.ORCID 0000-0003-3424-011X

Funding

National Dissemination of I-Corps@NCATS: Accelerating Translation through CommercializationUL1TR003096 · NCATS · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI GUTIERREZ, ORLANDO M, KIMBERLY, ROBERT P. · 2019 to 2023
$43.6M
Bridge2AI:Salutogenesis Data Generation ProjectOT2OD032644 · OD · WASHINGTON UNIVERSITY · PI BAXTER, SALLY LIU, CHUTE, CHRISTOPHER G · 2022 to 2025
$32.7M
PILOT STUDY--CLINICAL NUTRITION RESEARCHP30DK035816 · NIDDK · UNIVERSITY OF WASHINGTON · PI GREGORY J MORTON · 1986 to 2026
$30.4M
NCATS NIH HHS UL1 TR003096NIDDK NIH HHS P30 DK035816NIH HHS OT2 OD032644
6 · The paper itself

Abstract

The ability to understand and affect the course of complex, multi-system diseases like diabetes has been limited by a lack of well-designed, high-quality and large multimodal datasets. The NIH Bridge2AI AI-READI project (aireadi.org) aims to address this shortfall by generating an AI-ready dataset to support AI discoveries in type 2 diabetes mellitus (T2DM). This manual of procedures provides a detailed description of the AI-READI protocol.

Identifiers

PMID41959775
PMCPMC13060450

What OpenQuestion holds

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Registered trials

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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.