Evidence map›Paper›PMID 42844276›Full record

ArticleNature communications2026

A multitask framework for automated multi-frame right upper quadrant ultrasound interpretation and clinical decision support.

Haiman Guo, Cheng-Yi Li, Yuli Wang, Robin Wang, Yuwei Dai, Qinghai Peng, Danming Cao, Zhusi Zhong, Thao Vu, Linmei Zhao and 19 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. 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. 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

29 authors.

Haiman Guo *Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Cheng-Yi Li *Department of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.ORCID 0009-0000-9913-3695
Yuli Wang *Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0000-0003-3311-2810
Robin Wang *Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA.
Yuwei DaiDepartment of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. daiyuwei_1996@163.com.ORCID 0000-0003-4789-0242
Qinghai PengDepartment of Ultrasound, Second Xiangya Hospital, Central South University, Changsha, China.ORCID 0000-0002-5726-3202
Danming CaoDepartment of Ultrasound, Second Xiangya Hospital, Central South University, Changsha, China.
Zhusi ZhongDepartment of Diagnostic Imaging, Brown University Health, Providence, RI, USA.
Thao VuDepartment of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Linmei ZhaoDepartment of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Chengzhang ZhuSchool of Humanities, Central South University, Changsha, China.
Christopher TanDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Jacob SchickDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Stephen KwakDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Farzad SedaghatDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Javad AzadiDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
James FacciolaDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0009-0007-6252-2807
Jonathan FengDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Dilek OncelDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Ulrike HamperDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Alex ZhuDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Tej MehtaDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Melissa LeimkuehlerDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
Cheng Ting LinDepartment of Radiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID 0000-0003-0275-8037
Zhicheng JiaoDepartment of Diagnostic Imaging, Brown University Health, Providence, RI, USA.
Ihab KamelDepartment of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Jing WuDepartment of Radiology, Second Xiangya Hospital, Central South University, Changsha, China. wujingkiki622@gmail.com.
Li YangDepartment of Neurology, Second Xiangya Hospital, Central South University, Changsha, China.
Harrison BaiDepartment of Radiology, University of Colorado Anschutz Medical Campus, Aurora, CO, USA. harrison.bai@cuanschutz.edu.ORCID 0000-0002-7460-8866

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrasound is a cornerstone of emergency and hepatobiliary imaging, yet its interpretation remains highly operator-dependent and time-sensitive. Here, we present a multitask vision-language agent (VLM) developed to assist with right upper quadrant (RUQ) ultrasound interpretation across the diagnostic workflow. The system was trained on data from a single tertiary academic medical center (9189 cases, 594,099 images) and evaluated on datasets from two independent institutions (1704 cases, 90,616 images; and 108 cases, 3240 images). The agent integrates frame-level visual understanding with report-grounded language reasoning to perform three tasks: (i) classification of 16 clinical findings, (ii) generation of diagnostic reports, and (iii) surgical decision support based on ultrasound findings and clinical data. For classification, the model achieved macro areas under the receiver operating characteristic curve (AUROCs) of 0.820, 0.794, and 0.775 on the internal, University of Colorado, and Stanford cohorts, respectively, and an internal micro AUROC of 0.865. It also generated post-edited reports that were difficult for radiologists to distinguish from expert-written versions in blinded evaluations. The agent further predicted cholecystectomy using generated reports and clinical data. These results support further evaluation of vision-language models for improving diagnostic consistency, reporting efficiency, and surgical triage in ultrasound practice.

Indexed as

Decision Support Systems, ClinicalImage Interpretation, Computer-AssistedAlgorithmsHumansLiverROC CurveUltrasonography

Identifiers

PMID42844276
PMCPMC13646249

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.