Improving the Potential for Predicting Prostate Cancer Progression in Patients on Active Surveillance Using Explainable Artificial Intelligence.

Olga Vershinina, Nikita Sushentsev, Alexey Zaikin, Oleg Blyuss, Tristan Barrett, Mikhail Ivanchenko

Abstract read

In one paragraph

Article in Cancers, 2025. 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.

Synolitic Graph Neural Networks for MRI-Derived Radiomic-Based Prediction of Prostate Cancer Progression on Active Surveillance.Cancers · 2026
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.

Olga VershininaResearch Center in Artificial Intelligence, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia.ORCID 0000-0002-3917-9592

Nikita SushentsevDepartment of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge CB2 0QQ, UK.

Alexey ZaikinInstitute for Cognitive Neuroscience, University Higher School of Economics, Moscow 101000, Russia.ORCID 0000-0001-7540-1130

Oleg BlyussCentre for Cancer Screening, Prevention and Early Diagnosis, Wolfson Institute of Population Health, Queen Mary University of London, London EC1M 6BQ, UK.ORCID 0000-0002-0194-6389

Tristan BarrettDepartment of Radiology, Addenbrooke's Hospital and University of Cambridge, Cambridge CB2 0QQ, UK.

Mikhail IvanchenkoResearch Center in Artificial Intelligence, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Nizhny Novgorod 603022, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

active surveillanceexplainable artificial intelligencemachine learningMRI-derived radiomicsprogression predictionprostate cancer

Identifiers

PMID41300965

DOI10.3390/cancers17223598

PMCPMC12650280

What OpenQuestion holds

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LicenceCC BY

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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.