Evidence map›Paper›PMID 39857001›Full record

ArticleDiagnostics (Basel, Switzerland)2025

Adaptive Evolutionary Optimization of Deep Learning Architectures for Focused Liver Ultrasound Image Segmentation.

Ali Zifan, Katelyn Zhao, Madilyn Lee, Zihan Peng, Laura J Roney, Sarayu Pai, Jake T Weeks, Michael S Middleton, Ahmed El Kaffas, Jeffrey B Schwimmer and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diagnostics (Basel, Switzerland), 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.

  1. Tumour-focused 3D-2D registration in liver laparoscopy.International journal of computer assisted radiology and surgery · 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

11 authors.

Ali ZifanDivision of Gastroenterology and Hepatology, University of California San Diego, San Diego, CA 92093, USA.ORCID 0000-0003-0272-7492
Katelyn ZhaoDivision of Gastroenterology and Hepatology, University of California San Diego, San Diego, CA 92093, USA.
Madilyn LeeDivision of Gastroenterology and Hepatology, University of California San Diego, San Diego, CA 92093, USA.
Zihan PengDivision of Gastroenterology and Hepatology, University of California San Diego, San Diego, CA 92093, USA.
Laura J RoneyDivision of Gastroenterology and Hepatology, University of California San Diego, San Diego, CA 92093, USA.
Sarayu PaiDivision of Gastroenterology and Hepatology, University of California San Diego, San Diego, CA 92093, USA.
Jake T WeeksLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA.
Michael S MiddletonLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA.
Ahmed El KaffasLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA.
Jeffrey B SchwimmerDepartment of Pediatrics, Division of Gastroenterology, Hepatology, and Nutrition, University of California San Diego School of Medicine, La Jolla, CA 92093, USA.
Claude B SirlinLiver Imaging Group, Department of Radiology, University of California San Diego, San Diego, CA 92093, USA.

Funding

Quantitative Ultrasound To Diagnose Nonalcoholic Fatty Liver Disease in Children.R01DK135951 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI CLAUDE B SIRLIN, Jeffrey Barnett Schwimmer · 2024 to 2026
$2.1M
NIDDK NIH HHS R01 DK135951NIH HHS R01 DK135951
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

deep learning optimizationevolutionary genetic algorithmultrasound liver segmentation

Identifiers

PMID39857001
PMCPMC11763560

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.