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Prediction of Significant Liver Fibrosis

NCT06509230 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 700

Last updated 2024-07-19

No results posted yet for this study

Summary

The deep learning method based on convolutional neural network (CNN) was used to extract the relevant features of liver fibrosis classification from the multi-modal information of digital pathological sections, clinical parameters and biomarkers of a large number of existing cases of liver puncture, and the U-Net architecture of CNN was used to segment and extract the features of clinical medical images.

Conditions

  • Liver Fibrosis

Interventions

OTHER

The fibrosis grades were grouped without drug intervention

Sponsors & Collaborators

  • East China University of Science and Technology

    collaborator OTHER

  • Huang Haijun

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
60 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-07-20
Primary Completion
2024-12-31
Completion
2026-12-31

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06509230 on ClinicalTrials.gov