Evidence map›Paper›PMID 40619885›Full record

SynthesisTechnology in cancer research & treatment

Radiomics-Based Machine Learning for Determining

Haoru Wang, Yi Ji, Xin Chen, Ling He, Xiangming Fang, Jinhua Cai

Abstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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

  1. Pooled it
  2. Article
  3. Revista de neurologia · 2026
    Article
  4. Barriers to implementing AI in pediatric cancer imaging.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026
    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.

Haoru WangDepartment of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China.ORCID 0000-0003-2497-0872
Yi JiDepartment of Radiology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Xin ChenDepartment of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China.
Ling HeDepartment of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China.
Xiangming FangDepartment of Radiology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Jinhua CaiDepartment of Radiology, Children's Hospital of Chongqing Medical University, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Pediatrics, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IntroductionThe

Indexed as

Gene AmplificationMachine LearningNeuroblastomaN-Myc Proto-Oncogene ProteinBiomarkers, TumorChildHumansPrognosisRadiomicsBiomarkers, TumorMYCN protein, humanN-Myc Proto-Oncogene Proteinmeta-analysisMYCN oncogeneneuroblastomaradiomicssystematic review

Identifiers

PMID40619885
PMCPMC12235222

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.