Evidence map›Paper›PMID 38542194›Full record

ArticleInternational journal of molecular sciences2024

Identification of Genomic Signatures for Colorectal Cancer Survival Using Exploratory Data Mining.

Justin J Hummel, Danlu Liu, Erin Tallon, John Snyder, Wesley Warren, Chi-Ren Shyu, Jonathan Mitchem, Rene Cortese

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in International journal of molecular sciences, 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. Review
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.

Justin J HummelInstitute for Data Science and Informatics, University of Missouri, Columbia, MO 65212, USA.
Danlu LiuDepartment of Electrical Engineering and Computer Science, University of Missouri, Columbia, MO 65212, USA.
Erin TallonInstitute for Data Science and Informatics, University of Missouri, Columbia, MO 65212, USA.ORCID 0000-0003-1353-6632
John SnyderDepartment of Statistics, University of Missouri, Columbia, MO 65212, USA.
Wesley WarrenInstitute for Data Science and Informatics, University of Missouri, Columbia, MO 65212, USA.
Chi-Ren ShyuInstitute for Data Science and Informatics, University of Missouri, Columbia, MO 65212, USA.ORCID 0000-0001-9197-9522
Jonathan MitchemInstitute for Data Science and Informatics, University of Missouri, Columbia, MO 65212, USA.
Rene CorteseInstitute for Data Science and Informatics, University of Missouri, Columbia, MO 65212, USA.ORCID 0000-0001-9262-7828

Funding

Optimizing anti-tumor immunity for maximal therapeutic efficacy in Colorectal CancerIK2BX004346 · VA · LOUIS STOKES CLEVELAND VA MEDICAL CENTER · PI MITCHEM, JONATHAN B. · 2019 to 2024
–
BLRD VA IK2 BX004346
6 · The paper itself

Abstract

Clinicopathological presentations are critical for establishing a postoperative treatment regimen in Colorectal Cancer (CRC), although the prognostic value is low in Stage 2 CRC. We implemented a novel exploratory algorithm based on artificial intelligence (explainable artificial intelligence, XAI) that integrates mutational and clinical features to identify genomic signatures by repurposing the FoundationOne Companion Diagnostic (F1CDx) assay. The training data set (

Indexed as

Artificial IntelligenceColorectal NeoplasmsGene Expression Regulation, NeoplasticGenomicsHumansMutationNeoplasm Recurrence, Localcolorectal cancerexplainable artificial intelligenceF1CDx repurposinggenomic signatureprognosis

Identifiers

PMID38542194
PMCPMC10970183

What OpenQuestion holds

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LicenceCC BY
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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.