Evidence map›Paper›PMID 35052318›Full record

ArticleHealthcare (Basel, Switzerland)2022

Artificial Intelligence Analysis of Gene Expression Predicted the Overall Survival of Mantle Cell Lymphoma and a Large Pan-Cancer Series.

Joaquim Carreras, Naoya Nakamura, Rifat Hamoudi

Abstract read
In one paragraph

Article in Healthcare (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Article
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  7. Article
  8. Artificial intelligence and classification of mature lymphoid neoplasms.Exploration of targeted anti-tumor therapy · 2024
    Review
  9. Review
  10. The pathobiology of follicular lymphoma.Journal of clinical and experimental hematopathology : JCEH · 2023
    Article
  11. Review
  12. Article
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  15. Article
  16. Article
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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

3 authors.

Joaquim CarrerasDepartment of Pathology, Faculty of Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Japan.ORCID 0000-0002-6129-8299
Naoya NakamuraDepartment of Pathology, Faculty of Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara 259-1193, Japan.
Rifat HamoudiDepartment of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates.ORCID 0000-0002-1402-0868

Funding

AL-JALILA FOUNDATION AJF201741Ministry of Education, Culture, Sports, Science and Technology 18K15100Ministry of Education, Culture, Sports, Science and Technology KAKEN 15K19061THE SHARJAH RESEARCH ACADEMY MED001Tokai University TOKAI UNIVERSITY SCHOOL OF MEDICINE, RESEARCH INCENTIVE ASSISTANT PLAN 2021-B04University of Sharjah 1901090258
6 · The paper itself

Abstract

Mantle cell lymphoma (MCL) is a subtype of mature B-cell non-Hodgkin lymphoma characterized by a poor prognosis. First, we analyzed a series of 123 cases (GSE93291). An algorithm using multilayer perceptron artificial neural network, radial basis function, gene set enrichment analysis (GSEA), and conventional statistics, correlated 20,862 genes with 28 MCL prognostic genes for dimensionality reduction, to predict the patients' overall survival and highlight new markers. As a result, 58 genes predicted survival with high accuracy (area under the curve = 0.9). Further reduction identified 10 genes:

Indexed as

artificial intelligenceartificial neural networkdeep learninggene expressionimmuno-oncologymachine learningmantle cell lymphomaMCL35 assaymultilayer perceptronoverall survival

Identifiers

PMID35052318
PMCPMC8775707

What OpenQuestion holds

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Registered trials

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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.