Evidence map›Paper›PMID 35402965›Full record

ArticleIEEE open journal of engineering in medicine and biology2021

Prediction for the Risk of Multiple Chronic Conditions Among Working Population in the United States With Machine Learning Models.

Jingmei Yang, Xinglong Ju, Feng Liu, Onur Asan, Timothy Church, Jeff Smith

Open access · goldAbstract read
In one paragraph

Article in IEEE open journal of engineering in medicine and biology, 2021. 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
3.7field-weighted citation impact, top 6% of its field
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, 15 citations in OpenAlex.

  1. Article
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

6 authors at 4 institutions in 1 country.

Jingmei YangDivision of System EngineeringBoston University Boston MA 02246 USA.
Xinglong JuPrice College of BusinessUniversity of Oklahoma Norman OK 73019 USA.ORCID https://orcid.org/0000-0001-5213-2898
Feng LiuSchool of Systems and EnterprisesStevens Institute of Technology Hoboken NJ 07030 USA.ORCID https://orcid.org/0000-0002-5225-8199
Onur AsanSchool of Systems and EnterprisesStevens Institute of Technology Hoboken NJ 07030 USA.ORCID https://orcid.org/0000-0002-9239-3723
Timothy ChurchCatapult Health Inc. Dallas TX 75254 USA.
Jeff SmithCatapult Health Inc. Dallas TX 75254 USA.ORCID https://orcid.org/0000-0002-8603-1961
Catapult · USStevens Institute of Technology · USBoston University · USCornell University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

health informaticsmachine learningMultiple chronic conditionspredictive analysis

Identifiers

PMID35402965
PMCPMC8940207
OpenAlexW3201888594

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.