Evidence map›Paper›PMID 36120414›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2022

Usefulness of computed tomography textural analysis in renal cell carcinoma nuclear grading.

Israa Alnazer, Omar Falou, Pascal Bourdon, Thierry Urruty, Rémy Guillevin, Mohamad Khalil, Ahmad Shahin, Christine Fernandez-Maloigne

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

1 citing paper in PubMed.

  1. 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

8 authors.

Israa AlnazerUniversité de Poitiers, XLIM-ICONES, UMR CNRS 7252, Poitiers, France.ORCID https://orcid.org/0000-0003-4907-6084
Omar FalouLebanese University, AZM Center for Research in Biotechnology and Its Applications, EDST, Tripoli, Lebanon.ORCID https://orcid.org/0000-0002-3475-7891
Pascal BourdonUniversité de Poitiers, XLIM-ICONES, UMR CNRS 7252, Poitiers, France.
Thierry UrrutyUniversité de Poitiers, XLIM-ICONES, UMR CNRS 7252, Poitiers, France.
Rémy GuillevinLaboratoire commun CNRS/SIEMENS I3M, Poitiers, France.
Mohamad KhalilLebanese University, AZM Center for Research in Biotechnology and Its Applications, EDST, Tripoli, Lebanon.ORCID https://orcid.org/0000-0002-9814-1949
Ahmad ShahinLebanese University, AZM Center for Research in Biotechnology and Its Applications, EDST, Tripoli, Lebanon.
Christine Fernandez-MaloigneUniversité de Poitiers, XLIM-ICONES, UMR CNRS 7252, Poitiers, France.ORCID https://orcid.org/0000-0003-4818-9327

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

computer-aided diagnosismachine learningrenal cell carcinoma tumor gradingtexture

Identifiers

PMID36120414
PMCPMC9467905

What OpenQuestion holds

Textmetadata
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.