Evidence map›Paper›PMID 38126237›Full record

ArticleCirculation. Heart failure2024

Deep Learning and Biased Prediction: More Questions Than Answers?

Michael A Rosenberg

Abstract readEditorialComment
In one paragraph

Article in Circulation. Heart failure, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

1 author.

Michael A RosenbergDivision of Cardiology, Cardiac Electrophysiology Section and Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora.

Funding

Development of End-To-End Clinical Decision Support Tools To Prevent Cardiotoxic Drug ResponseR01HL146824 · NHLBI · UNIVERSITY OF COLORADO DENVER · PI ROSENBERG, MICHAEL A · 2020 to 2024
$3.9M
NHLBI NIH HHS R01 HL146824
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Deep LearningHeart FailureHumansMachine Learningbiasbiometrydeep learningEditorialsgoals

Identifiers

PMID38126237
PMCPMC10842806

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.