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Research on the Application Value of Temporal Sequence-related Deep LearningNetworks and Large Language Models in .Contrast-enhanced Ultrasoundiagnosis and Therapeutic Effect Prediction of Hepatic Focal Lesions

Research on the Application Value of Temporal Sequence-related Deep LearningNetworks and Large Language Models in .Contrast-enhanced Ultrasoundiagnosis and Therapeutic Effect Prediction of Hepatic Focal Lesions

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500112375
Enrollment
Unknown
Registered
2025-11-13
Start date
2025-12-01
Completion date
Unknown
Last updated
2025-11-17

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Hepatic Focal Lesions

Interventions

Gold Standard:Surgery or biopsy
Index test:Ultrasound images, artificial intelligence methods

Sponsors

Zhongshan hospital, Fudan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: Inclusion criteria: (1) Patients aged 18 to 80 years who underwent liver contrast-enhanced ultrasound examination at our hospital for liver focal lesions and both inpatients and outpatients; (2) Patients who agreed to participate in this trial and all signed the informed consent form.

Exclusion criteria

Exclusion criteria: Exclusion criteria: (1) Insufficient image data. (2) Poor image quality.

Design outcomes

Primary

MeasureTime frame
Multimodal ultrasound diagnostic results;Artificial Intelligence Network Model;AUC;Accuracy;Sensitivity;Specificity;—

Countries

China

Contacts

Public ContactHuixiong Xu

Zhongshan hospital, Fudan University

xuhuixiong@126.com+86 21 6404 1990

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026