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Artificial intelligence assisted accurate diagnosis and treatment of liver lesions by ultrasound and comparison with CT / MR

Artificial intelligence assisted accurate diagnosis and treatment of liver lesions by ultrasound and comparison with CT / MR

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2100048674
Enrollment
Unknown
Registered
2021-07-12
Start date
2021-09-01
Completion date
Unknown
Last updated
2022-03-21

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

Conditions

liver lesions

Interventions

Gold Standard:Biopsy or postoperative pathological results, clinical diagnosis.
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ultrasound&#32
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diagnosis

Sponsors

The First Affiliated Hospital of Sun Yat-Sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Aged > 18 years old; 2.Have liver occupying image, examination and pathological data.

Exclusion criteria

Exclusion criteria: 1.The pathological or clinical diagnosis is not clear; 2.Imaging data are missing or incomplete.

Design outcomes

Primary

MeasureTime frame
accuracy;sensitivity;specificity;—

Countries

China

Contacts

Public ContactWang Wei

The First Affiliated Hospital of Sun Yat-Sen University

wangwei73@mail.sysu.edu.cn+86 20 87765183

Outcome results

None listed

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