Evidence map›Paper›PMID 41782820›Full record

ArticleiScience2026

Development of immune-derived molecular markers for coronary heart disease via multimachine learning.

Hao Wang, Chong Du, Tongtong Yang, Wenjing Wang, Liuhua Zhou, Lingfeng Gu, Sibo Wang, Wei Gao, Jianjun Yan, Liansheng Wang and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in iScience, 2026. 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

11 authors.

Hao WangDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Chong DuDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Tongtong YangDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Wenjing WangDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Liuhua ZhouDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Lingfeng GuDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Sibo WangDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Wei GaoDepartment of Geriatrics, Zhongda Hospital, School of Medicine, Southeast University, Nanjing 210029, China.
Jianjun YanThe People's Hospital of Rugao, Affiliated Rugao Hospital of Xinglin College, Nantong University, Nantong 226000, China.
Liansheng WangDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.
Qiming WangDepartment of Cardiology, the First Affiliated Hospital with Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronary artery disease (CAD) is a major cardiovascular disorder primarily caused by coronary atherosclerosis, and early, sensitive diagnosis remains a clinical challenge. In this study, we developed a novel diagnostic model for CAD and explored potential therapeutic agents. CAD-associated datasets were obtained from the Gene Expression Omnibus. Using multimachine learning algorithms, 32 CAD- and immune-related characteristic genes were identified, and the resulting diagnostic model demonstrated excellent diagnostic performance. Immune cell infiltration analysis suggested that CD8

Indexed as

cell biologyhealth sciencesImmunology

Identifiers

PMID41782820
PMCPMC12955253

What Socratic holds

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Registered trials

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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 Socratic graph.