Evidence map›Paper›PMID 40658759›Full record

ArticleCirculation2025

The Promise and Peril of Learning Algorithms and Predictive Models in Clinical Decision Support: Be Careful What You Train For.

Trejeeve Martyn, Mazen Hanna, Fatima Rodriguez

Abstract read
In one paragraph

Article in Circulation, 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

3 authors.

Trejeeve MartynGeorge and Linda Kaufman Center for Heart Failure, Heart Vascular Thoracic Institute (T.M., M.H.), Cleveland Clinic, OH.
Mazen HannaGeorge and Linda Kaufman Center for Heart Failure, Heart Vascular Thoracic Institute (T.M., M.H.), Cleveland Clinic, OH.
Fatima RodriguezDivision of Cardiovascular Medicine and Cardiovascular Institute, Stanford University, CA (F.R.).ORCID 0000-0002-5226-0723

Funding

Opportunistic Atherosclerotic Cardiovascular Disease Risk Estimation at Abdominal CTs with Robust and Unbiased Deep LearningR01HL167974 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 2023 to 2026
$2.4M
Novel Incidental Calcium Evaluation (NICE)R01HL169345 · NHLBI · STANFORD UNIVERSITY · PI Imon Banerjee, Akshay Chaudhari · 2024 to 2026
$2.1M
Adherence Determinants in the Health Electronic Record Evaluation of Statins (ADHERES)R01HL168188 · NHLBI · STANFORD UNIVERSITY · PI Fatima Rodriguez · 2024 to 2026
$2.1M
NHLBI NIH HHS R01 HL167974NHLBI NIH HHS R01 HL168188NHLBI NIH HHS R01 HL169345
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial intelligenceclinical decision-makingmachine learning

Identifiers

PMID40658759
PMCPMC12262177

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.