Evidence map›Paper›PMID 41868687›Full record

ArticleAmerican journal of nuclear medicine and molecular imaging2026

CNN-based detection of pediatric lymphoma on whole body [

Shashi B Singh, Yashas Ullas Lokesha, Hongzhi Wang, Michael Joseph Barrow, Ricarda von Kruechten, Iryna Vasyliv, Amir Hossein Sarrami, Joy Tzung-Yu Wu, Lucia Baratto, Lisa Christine Adams and 6 more

Abstract read
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In one paragraph

Article in American journal of nuclear medicine and molecular imaging, 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

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

16 authors.

Shashi B SinghDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Yashas Ullas LokeshaDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Hongzhi WangIBM Almaden Research Center 650 Harry Road, San Jose, CA 95120, USA.
Michael Joseph BarrowDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Ricarda von KruechtenDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Iryna VasylivDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Amir Hossein SarramiDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Joy Tzung-Yu WuDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Lucia BarattoDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Lisa Christine AdamsDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Hyun Gi KimDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Jason WongDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Tie LiangDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Sergios GatidisDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.
Tanveer Syeda-MahmoodIBM Almaden Research Center 650 Harry Road, San Jose, CA 95120, USA.
Heike E Daldrup-LinkDepartment of Radiology, Stanford University School of Medicine Stanford, CA 94305, USA.

Funding

Advanced Imaging Tools to Assess Cancer Therapeutics in Pediatric PatientsR01CA269231 · NCI · STANFORD UNIVERSITY · PI Heike Elizabeth Daldrup-Link · 2022 to 2026
$3.5M
NCI NIH HHS R01 CA269231
6 · The paper itself

Abstract

We assessed the performance of a deep convolutional neural network (CNN) in detecting pediatric lymphoma lesions on [

Indexed as

artificial Intelligence (AI)convolutional neural network (CNN)Lymphomapediatricpositron emission tomography/magnetic resonance imaging (PET/MRI)

Identifiers

PMID41868687
PMCPMC13003233

What OpenQuestion holds

Textmetadata
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 OpenQuestion graph.