Evidence map›Paper›PMID 39669009›Full record

ArticleJournal of medical imaging (Bellingham, Wash.)2024

Radiomics for differentiation of somatic

Mena Shenouda, Abbas Shaikh, Ilana Deutsch, Owen Mitchell, Hedy L Kindler, Samuel G Armato

Abstract read
In one paragraph

Article in Journal of medical imaging (Bellingham, Wash.), 2024. 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. Radiomics for differentiation of somaticJournal of medical imaging (Bellingham, Wash.) · 2024
    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.

Mena ShenoudaThe University of Chicago, Department of Radiology, Chicago, Illinois, United States.ORCID https://orcid.org/0000-0003-3286-1350
Abbas ShaikhRice University, Houston, Texas, United States.ORCID https://orcid.org/0009-0001-4654-7154
Ilana DeutschNorthwestern University, Evanston, Illinois, United States.ORCID https://orcid.org/0009-0005-0111-8435
Owen MitchellThe University of Chicago, Department of Medicine, Chicago, Illinois, United States.ORCID https://orcid.org/0000-0001-5601-731X
Hedy L KindlerThe University of Chicago, Department of Medicine, Chicago, Illinois, United States.
Samuel G ArmatoThe University of Chicago, Department of Radiology, Chicago, Illinois, United States.ORCID https://orcid.org/0000-0002-5428-7997

Funding

Protected Radiomics Analysis Commons for Deep Learning in Biomedical DiscoveryS10OD025081 · OD · UNIVERSITY OF CHICAGO · PI GIGER, MARYELLEN L. · 2018 to 2018
$339k
NIH HHS S10 OD025081
6 · The paper itself

Abstract

Purpose: The BRCA1-associated protein 1 ( Approach: A cohort of 149 patients with PM and known somatic Results: A decision tree classifier achieved the highest overall AUC value of 0.69 (95% confidence interval: 0.60 and 0.77). The features selected most frequently through the LOOCV were all second-order (gray-level co-occurrence or gray-level size zone matrices) and were extracted from images with an applied transformation. Conclusions: This proof-of-concept work demonstrated the potential of radiomics to differentiate among

Indexed as

BRCA1-associated protein 1classificationcomputed tomography scandeep learningmesotheliomasomatic mutationU-Net

Identifiers

PMID39669009
PMCPMC11633667

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.