Evidence map›Paper›PMID 39766765›Full record

ArticleGenes2024

Leveraging Bioinformatics and Machine Learning for Identifying Prognostic Biomarkers and Predicting Clinical Outcomes in Lung Adenocarcinoma.

Kaida Cai, Wenzhi Fu, Hanwen Liu, Xiaofang Yang, Zhengyan Wang, Xin Zhao

Abstract read
In one paragraph

Article in Genes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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.

Kaida CaiDepartment of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing 210009, China.ORCID 0000-0003-2262-3869
Wenzhi FuDepartment of Statistics and Actuarial Science, School of Mathematics, Southeast University, Nanjing 211189, China.ORCID 0009-0009-0780-5227
Hanwen LiuDepartment of Statistics and Actuarial Science, School of Mathematics, Southeast University, Nanjing 211189, China.
Xiaofang YangDepartment of Statistics and Actuarial Science, School of Mathematics, Southeast University, Nanjing 211189, China.
Zhengyan WangDepartment of Statistics and Actuarial Science, School of Mathematics, Southeast University, Nanjing 211189, China.
Xin ZhaoDepartment of Statistics and Actuarial Science, School of Mathematics, Southeast University, Nanjing 211189, China.ORCID 0000-0002-3604-1643

Funding

Fundamental Research Funds for the Central Universities 2242023K40012Fundamental Research Funds for the Central Universities 2242023R40055Fundamental Research Funds for the Central Universities MCCSE2023B04National Natural Science Foundation of China 12201108National Natural Science Foundation of China 12301334Natural Science Foundation of Jiangsu Province BK20230804
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Adenocarcinoma of LungBiomarkers, TumorComputational BiologyLung NeoplasmsMachine LearningProtein Interaction MapsFemaleGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateMalePrognosisBiomarkers, Tumorfeature selectionlung adenocarcinomamachine learningprognostic biomarkersRNA sequencing data

Identifiers

PMID39766765
PMCPMC11675206

What Socratic 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 Socratic graph.