Evidence map›Paper›PMID 38993563›Full record

ArticleInternational journal of biological sciences2024

Machine Learning-based Framework Develops a Tumor Thrombus Coagulation Signature in Multicenter Cohorts for Renal Cancer.

Tao Feng, Yue Wang, Wei Zhang, Tingting Cai, Xi Tian, Jiaqi Su, Zihao Zhang, Shengfeng Zheng, Shiqi Ye, Bo Dai and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of biological sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
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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

15 authors.

Tao FengQingdao Institute, School of Life Medicine, Department of Urology, Fudan University Shanghai Cancer Center, Fudan University, Qingdao, 266500, China.
Yue WangDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Wei ZhangDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Tingting CaiDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Xi TianDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Jiaqi SuDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Zihao ZhangQingdao Institute, School of Life Medicine, Department of Urology, Fudan University Shanghai Cancer Center, Fudan University, Qingdao, 266500, China.
Shengfeng ZhengQingdao Institute, School of Life Medicine, Department of Urology, Fudan University Shanghai Cancer Center, Fudan University, Qingdao, 266500, China.
Shiqi YeDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Bo DaiDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Ziliang WangCentral Laboratory, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, 274 Middle Zhijiang Road, Shanghai 200071, China.
Yiping ZhuDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Hailiang ZhangDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Kun ChangDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.
Dingwei YeDepartment of Urology, State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University Shanghai Cancer Center, Fudan University, Shanghai, 200433, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsMachine LearningCohort StudiesHumansPrognosisThrombosisCYP51A1immunotherapyMachine learningrenal cell carcinomaTumor thrombus

Identifiers

PMID38993563
PMCPMC11234220

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.