Evidence map›Paper›PMID 40636352›Full record

ReviewiLIVER2022

Artificial intelligence-based ultrasound imaging technologies for hepatic diseases.

Longfei Ma, Rui Wang, Qiong He, Lijie Huang, Xingyue Wei, Xu Lu, Yanan Du, Jianwen Luo, Hongen Liao

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in iLIVER, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. Application and prospects of AI-based radiomics in ultrasound diagnosis.Visual computing for industry, biomedicine, and art · 2023
    Review
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

9 authors.

Longfei MaDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Rui WangDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Qiong HeDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Lijie HuangDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Xingyue WeiDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Xu LuGraduate School at Shenzhen, Tsinghua University, Shenzhen, 518055, Guangdong, China.
Yanan DuDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Jianwen LuoDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.
Hongen LiaoDepartment of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, 100084, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ultrasound (US) imaging is a non-invasive, real-time, economical, and convenient imaging modality that has been widely used in diagnosing and treating hepatic diseases. Artificial intelligence (AI) technology can predict or make decisions based on the experience of clinical experts and knowledge obtained from training data. This technology can help clinicians improve the detection efficiency and evaluate hepatic diseases, promote clinical treatment of the liver, and predict the response of the liver after treatment. This review summarizes the current rapid development of US technology and related AI methods in the diagnosis and treatment of hepatic diseases. Covered topics include steatosis grading, fibrosis staging, detection of focal liver lesions, US image segmentation, multimodal image registration, and other applications. At present, the field of AI in US imaging is still in its early stages. With the future progress of AI technology, AI-based US imaging can further improve diagnosis, reduce medical costs, and optimize US-based clinical workflow. This technology has broad prospects for application to hepatic diseases.

Indexed as

Artificial intelligenceDiagnosis and treatmentHepatic diseasesUltrasound imaging

Identifiers

PMID40636352
PMCPMC12212738

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.