Evidence map›Paper›PMID 36968604›Full record

ArticleFrontiers in genetics2023

Bayesian feature selection for radiomics using reliability metrics.

Katherine Shoemaker, Rachel Ger, Laurence E Court, Hugo Aerts, Marina Vannucci, Christine B Peterson

Full text read
In one paragraph

Article in Frontiers in genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A Review.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2025
    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.

Katherine ShoemakerDepartment of Mathematics and Statistics, University of Houston-Downtown, Houston, TX, United States.
Rachel GerDepartment of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States.
Laurence E CourtDepartment of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.
Hugo AertsArtificial Intelligence in Medicine (AIM) Program, Mass General Brigham, Harvard Medical School, Boston, MA, United States.
Marina VannucciDepartment of Statistics, Rice University, Houston, TX, United States.
Christine B PetersonDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, United States.

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Training Program in Biostatistics for Cancer ResearchT32CA096520 · NCI · RICE UNIVERSITY · PI KIMMEL, MAREK, YUAN, YING · 2003 to 2023
$4.5M
NCI NIH HHS P30 CA016672NCI NIH HHS T32 CA096520
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Bayesian modelingclassificationprobit priorquantitative imagingradiomicsvariable selection

Identifiers

PMID36968604
PMCPMC10030957

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read20
table measurements read8
reference markers read18
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.