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Prediction of Significant Liver Fibrosis

RECRUITINGSponsored by Huang Haijun
Actively Recruiting
SponsorHuang Haijun
Started2024-07-20
Est. completion2024-12-31
Eligibility
Age18 Years – 60 Years
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT06509230

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.

Eligibility

Age: 18 Years – 60 YearsHealthy volunteers accepted
Inclusion Criteria:

1. Age of 18-60 years old
2. The diagnosis of chronic hepatitis B is in line with the diagnostic criteria of China's 2019 Chronic Hepatitis B Prevention and Treatment Guidelines, and the diagnosis of non-alcoholic fatty liver is in line with the Asian Pacific Hepatology Association guidelines
3. Imaging showed no liver cancer

Exclusion Criteria:

1. There are contraindications for liver biopsy
2. Liver pathology did not meet the criteria

Conditions2

Liver DiseaseLiver Fibrosis

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