Evidence map›Paper›PMID 40427119›Full record

ArticleCancers2025

The Association Between Heatmap Position and the Diagnostic Accuracy of Artificial Intelligence for Colorectal Polyp Diagnosis.

Ayla Thijssen, Nikoo Dehghani, Ruud W M Schrauwen, Eric T P Keulen, Eveline J A Rondagh, Mark H P van Avesaat, Khalida Soufidi, Ankie Reumkens, Paul H A Bours, Quirine E W van der Zander and 4 more

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Article in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Ayla ThijssenDepartment of Gastroenterology and Hepatology, Maastricht University Medical Center+, 6202 AZ Maastricht, The Netherlands.ORCID 0000-0002-4488-4333
Nikoo DehghaniDepartment of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.ORCID 0009-0008-7225-3118
Ruud W M SchrauwenDepartment of Gastroenterology and Hepatology, Bernhoven Hospital, Nistelrodeseweg 10, 5406 PT Uden, The Netherlands.ORCID 0000-0002-4680-3699
Eric T P KeulenDepartment of Gastroenterology and Hepatology, Zuyderland Medical Center, Dr. H. van der Hoffplein 1, 6162 AP Sittard-Geleen, The Netherlands.ORCID 0000-0001-6666-8773
Eveline J A RondaghDepartment of Gastroenterology and Hepatology, Zuyderland Medical Center, Dr. H. van der Hoffplein 1, 6162 AP Sittard-Geleen, The Netherlands.
Mark H P van AvesaatDepartment of Gastroenterology and Hepatology, Zuyderland Medical Center, Dr. H. van der Hoffplein 1, 6162 AP Sittard-Geleen, The Netherlands.
Khalida SoufidiDepartment of Gastroenterology and Hepatology, Zuyderland Medical Center, Dr. H. van der Hoffplein 1, 6162 AP Sittard-Geleen, The Netherlands.
Ankie ReumkensDepartment of Gastroenterology and Hepatology, Zuyderland Medical Center, Dr. H. van der Hoffplein 1, 6162 AP Sittard-Geleen, The Netherlands.ORCID 0000-0002-3326-3793
Paul H A BoursDepartment of Gastroenterology and Hepatology, Zuyderland Medical Center, Dr. H. van der Hoffplein 1, 6162 AP Sittard-Geleen, The Netherlands.
Quirine E W van der ZanderDepartment of Gastroenterology and Hepatology, Maastricht University Medical Center+, 6202 AZ Maastricht, The Netherlands.ORCID 0000-0002-8640-5521
Peter H N de WithDepartment of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.
Bjorn WinkensDepartment of Methodology and Statistics, Maastricht University, 6202 AZ Maastricht, The Netherlands.ORCID 0000-0002-6747-6228
Fons van der SommenDepartment of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands.ORCID 0000-0002-3593-2356
Erik J SchoonGROW Research Institute for Oncology and Reproduction, Maastricht University, 6202 AZ Maastricht, The Netherlands.

Funding

Dutch Cancer Society 12639
6 · The paper itself

Abstract

BACKGROUND/

objectivesArtificial intelligence (AI) algorithms for diagnosing colorectal polyps are emerging but not yet widely used. Trust in AI is lacking and could be improved by visually explainable AI, such as heatmaps. This study aims to investigate the association between heatmap position and AI accuracy for the endoscopic characterization of colorectal polyps.

methodsFour AI algorithms diagnosed 2133 prospectively collected images of 376 colorectal polyps from two hospitals, using histopathology as the gold standard. Heatmap position was compared to the human-annotated polyp position. Generalized estimating equations were used to assess the association between heatmap position and a correct AI diagnosis.

resultsHigher percentages of heatmap covering the colorectal polyp were associated with correct diagnoses in all four algorithms (OR 1.013 [95% CI 1.006-1.019], OR 1.025 [95% CI 1.011-1.039], OR 1.038 [95% CI 1.024-1.053], and OR 1.039 [95% CI 1.020-1.058]-all

conclusionsHigher percentages of heatmap covering the polyp were associated with correct diagnoses of four AI algorithms. This indicates that it is clinically relevant to strive for AI predictions with heatmaps covering as much colorectal polyp tissue as possible. Knowing how to interpret heatmaps could increase trust in AI and, with that, benefit the implementation of AI in clinical practice.

Indexed as

colonoscopycolorectal polypscomputer-aided diagnosisvisually explainable artificial intelligence

Identifiers

PMID40427119
PMCPMC12109631

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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.