Evidence map›Paper›PMID 40708014›Full record

ArticleGenome biology2025

Explainable deep learning for stratified medicine in inflammatory bowel disease.

Nora Verplaetse, Piero Fariselli, Yves Moreau, Daniele Raimondi

Abstract read
In one paragraph

Article in Genome biology, 2025. 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. Article
  2. Review
  3. 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

4 authors.

Nora VerplaetseESAT-STADIUS, KU Leuven, Leuven, 3001, Belgium. noraverplaetse@gmail.com.
Piero FariselliDepartment of Medical Sciences, University of Torino, Torino, 10123, Italy.
Yves MoreauESAT-STADIUS, KU Leuven, Leuven, 3001, Belgium.
Daniele RaimondiESAT-STADIUS, KU Leuven, Leuven, 3001, Belgium.

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GABRIEL, STACEY, LANDER, ERIC S · 2004 to 2015
$568.6M
Fonds Wetenschappelijk Onderzoek 12Y5623NNHGRI NIH HHS U54 HG003067
6 · The paper itself

Abstract

Moving from a one-size-fits-all to an individual approach in precision medicine requires a deeper understanding of disease molecular mechanisms. Especially in heterogeneous complex diseases such as inflammatory bowel disease (IBD), better molecular stratification will help select the correct therapy. For this, we build end-to-end biologically sparsified neural network architectures for IBD subtyping based on whole exome sequence representations with gene-level and variant-level resolution. By moving beyond univariate methods, we capitalize on the model's ability to extract complex molecular patterns to improve prediction. Model interpretation identifies the most predictive pathways, genes, and variants, uncovering important intestinal barrier, immunological, and microbiome factors.

Indexed as

Deep LearningInflammatory Bowel DiseasesPrecision MedicineExome SequencingHumansNeural Networks, ComputerGenome interpretationMachine learningNeural networks

Identifiers

PMID40708014
PMCPMC12291258

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.