Evidence map›Paper›PMID 34414250›Full record

ArticleJournal of health economics and outcomes research2021

Using Deep Learning to Identify High-Risk Patients with Heart Failure with Reduced Ejection Fraction.

Zhibo Wang, Xin Chen, Xi Tan, Lingfeng Yang, Kartik Kannapur, Justin L Vincent, Garin N Kessler, Boshu Ru, Mei Yang

Abstract read
In one paragraph

Article in Journal of health economics and outcomes research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Zhibo WangMerck & Co., Inc., Kenilworth, NJ, USA; College of Engineering and Computer Science, University of Central Florida, Orlando, FL, USA.
Xin ChenMerck & Co., Inc., Kenilworth, NJ, USA.
Xi TanMerck & Co., Inc., Kenilworth, NJ, USA.
Lingfeng YangMerck & Co., Inc., Kenilworth, NJ, USA.
Kartik KannapurAmazon Web Services Inc., Seattle, WA, USA.
Justin L VincentAmazon Web Services Inc., Seattle, WA, USA.
Garin N KesslerAmazon Web Services Inc., Seattle, WA, USA; Georgetown University, Seattle, WA, USA.
Boshu RuMerck & Co., Inc., Kenilworth, NJ, USA.
Mei YangMerck & Co., Inc., Kenilworth, NJ, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

deep learningheart failurehospitalizationsmachine learningreadmissionsworsening events

Identifiers

PMID34414250
PMCPMC8322198

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.