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Research and Application of Key Multimodal Deep Learning Technologies for Intelligent Auxiliary Diagnosis of Liver Cancer

Research and Application of Key Multimodal Deep Learning Technologies for Intelligent Auxiliary Diagnosis of Liver Cancer

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117328
Enrollment
Unknown
Registered
2026-01-22
Start date
2026-03-01
Completion date
Unknown
Last updated
2026-01-27

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

Conditions

Early Detection and High-Risk Factor Analysis of Hepatocellular Carcinoma

Interventions

Observational group:None

Sponsors

The First Hospital Of Jiaxing
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Completion of all required physical examinations; 2.Patients provide written informed consent for research use of their data; 3.Age > 18 years.

Exclusion criteria

Exclusion criteria: 1.History of Other Malignant Tumors in the Liver; 2.Incomplete Required Medical Examination Data; 3.People with communication barriers;

Design outcomes

Primary

MeasureTime frame
Demographic information (gender, age, hypertension, diabetes, hepatitis, ascites);Laboratory test information (including AFP, ALB, PT, INR, AST, ALT, creatinine, TBIL, Child-Pugh score, complete blood count, blood glucose, and lipid profile, etc.).;;Imaging examination report (including number of tumors, maximum diameter, BCLC stage, extrahepatic metastasis, vascular invasion, etc.).;Model performance metrics (including accuracy, sensitivity, specificity, and other algorithm evaluation indicators of the decision support system).;

Countries

China

Contacts

Public ContactZhou Hongkun

The First Hospital Of Jiaxing

0805xueming@163.com+86 10 13586300

Outcome results

None listed

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