Evidence map›Paper›PMID 35204639›Full record

ArticleDiagnostics (Basel, Switzerland)2022

Combining Hepatic and Splenic CT Radiomic Features Improves Radiomic Analysis Performance for Liver Fibrosis Staging.

Yunchao Yin, Derya Yakar, Rudi A J O Dierckx, Kim B Mouridsen, Thomas C Kwee, Robbert J de Haas

Abstract read
In one paragraph

Article in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 3 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

15 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Review
  13. Review
  14. Article
  15. 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.

Yunchao YinDepartment of Radiology, Medical Imaging Center Groningen, University of Groningen, University Medical Center Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands.ORCID 0000-0002-5790-484X
Derya YakarDepartment of Radiology, Medical Imaging Center Groningen, University of Groningen, University Medical Center Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands.ORCID 0000-0002-4920-9441
Rudi A J O DierckxDepartment of Radiology, Medical Imaging Center Groningen, University of Groningen, University Medical Center Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands.
Kim B MouridsenDepartment of Radiology, Medical Imaging Center Groningen, University of Groningen, University Medical Center Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands.
Thomas C KweeDepartment of Radiology, Medical Imaging Center Groningen, University of Groningen, University Medical Center Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands.
Robbert J de HaasDepartment of Radiology, Medical Imaging Center Groningen, University of Groningen, University Medical Center Groningen, P.O. Box 30001, 9700 RB Groningen, The Netherlands.ORCID 0000-0002-4915-6781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

artificial intelligencelivermachine learningmultidetector computed tomographyradiomics

Identifiers

PMID35204639
PMCPMC8870954

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.