Evidence map›Paper›PMID 40837114›Full record

ArticleData science in science2025

Enhancing Health Research with Machine Learning: Practical Case Studies Using the

Jonathan R Holt, Stefanee Tillman, Javan Carter, Edward Preble, Sheryl C Cates, Daniel Brannock, Michael Long, John McCarthy, Leslie Zapata Leiva, Jamboor K Vishwanatha and 6 more

Abstract read
In one paragraph

Article in Data science in science, 2025. 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

16 authors.

Jonathan R HoltRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Stefanee TillmanRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Javan CarterRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Edward PrebleRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Sheryl C CatesRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Daniel BrannockRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Michael LongRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
John McCarthyRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Leslie Zapata LeivaRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Jamboor K VishwanathaThe University of North Texas Health Science Center, Fort Worth, TX 76107.
Toufeeq SyedThe University of Texas Health Science Center at Houston TX 77225-0036.
Legand BurgeHoward University, Department of Electrical Engineering and Computer Science, 2400 6thSt NW, Washington, DC 20059.
Robert T MalletThe University of North Texas Health Science Center, Fort Worth, TX 76107.
Shelly KowalczykThe Maya Tech Corporation, 8401 Colesville Rd #430, Silver Spring, MD 20910.
Jennifer D UhrigRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.
Megan A LewisRTI International, 3040 East Cornwallis Rd, RTP, NC 27709.

Funding

AIM-AHEAD Coordinating Center - All Four CoresOT2OD032581 · OD · UNIVERSITY OF NORTH TEXAS HLTH SCI CTR · PI Paul Avillach, Bettina M. Beech · 2021 to 2026
$168.7M
All of Us Research Program Engagement and Retention InnovatorsOT2OD028395 · OD · RESEARCH TRIANGLE INSTITUTE · PI JENNIFER D UHRIG · 2020 to 2026
$45.1M
NIH HHS OT2 OD028395NIH HHS OT2 OD032581
6 · The paper itself

Abstract

Machine learning is revolutionizing health research by enabling scalable analysis across complex datasets. The

Indexed as

All of Us Researcher Workbenchartificial intelligenceelectronic health recordsmachine learningprofessional developmenttraining program

Identifiers

PMID40837114
PMCPMC12362663

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.