Evidence map›Paper›PMID 42051572›Full record

ArticlemedRxiv : the preprint server for health sciences2026

Development and Validation of a Multimodal AI-Based Model for Predicting Post-Prostatectomy Treatment Outcomes from Baseline Biparametric Prostate MRI.

Benjamin D Simon, Esra Akcicek, Stephanie A Harmon, Lei Clifton, Anshul Thakur, Sandeep Gurram, David Clifton, Bradford J Wood, Ali Devrim Karaosmanoglu, Peter L Choyke and 3 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2026. 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
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

13 authors.

Benjamin D SimonMolecular Imaging Branch, NCI, NIH, Bethesda, MD, USA.ORCID 0000-0002-8658-9711
Esra AkcicekDepartment of Radiology, Hacettepe University, Ankara, Turkey.
Stephanie A HarmonMolecular Imaging Branch, NCI, NIH, Bethesda, MD, USA.
Lei CliftonNuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID 0000-0001-5595-8468
Anshul ThakurInstitute of Biomedical Engineering, University of Oxford, Oxford, UK.
Sandeep GurramUrologic Oncology Branch, NCI, NIH, Bethesda, MD, USA.
David CliftonInstitute of Biomedical Engineering, University of Oxford, Oxford, UK.
Bradford J WoodCenter for Interventional Oncology, NCI, NIH, Bethesda, MD, USA.ORCID 0000-0002-4297-0051
Ali Devrim KaraosmanogluDepartment of Radiology, Hacettepe University, Ankara, Turkey.
Peter L ChoykeMolecular Imaging Branch, NCI, NIH, Bethesda, MD, USA.
Deniz AkataDepartment of Radiology, Hacettepe University, Ankara, Turkey.
Peter A PintoUrologic Oncology Branch, NCI, NIH, Bethesda, MD, USA.
Baris TürkbeyMolecular Imaging Branch, NCI, NIH, Bethesda, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PCa) is the second most common cancer and cause of cancer death in American men. Existing risk prediction methods have limited accuracy and reproducibility, resulting in difficulty in predicting disease severity. We demonstrate the development and external validation of an automated multimodal artificial intelligence algorithm using biparametric MRI (bpMRI) and clinical covariates for predicting biochemical recurrence (BCR) after radical prostatectomy (RP) in PCa patients. Development cohort included 80% of patients from center 1 (

Indexed as

artificial intelligencebiochemical recurrenceMRIprostate cancerradical prostatectomyradiomics

Identifiers

PMID42051572
PMCPMC13119357

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.