Predicting prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure from longitudinal ultrasound images using a multi-task deep learning approach
The Siamese U-Net emerges as a promising tool in predicting prognosis for HBV-ACLF, thereby enhancing clinical decision-making and improving patient outcomes.
Authors
- Pan Xu (ORCID: https://orcid.org/0000-0002-1931-0581)
- Yukun Kuang (ORCID: https://orcid.org/0000-0002-3342-4489)
- Aiyun Zhou (ORCID: https://orcid.org/0000-0001-6875-4931)
- Songsong Yuan
- Xinchun Yuan (ORCID: https://orcid.org/0000-0003-0516-965X)
- Xingzhi Huang (ORCID: https://orcid.org/0000-0002-5458-4852)
- Yaohui Li (ORCID: https://orcid.org/0000-0002-2982-0059)
Institutions
- Nanchang University (CN)
- First Affiliated Hospital of Jiangxi Medical College (CN)
- First Affiliated Hospital of Nanchang University (CN)
Publication Details
- Journal
- Annals of Medicine
- Published
- 2025-08-26
- DOI
- https://doi.org/10.1080/07853890.2025.2551819
- Citations
- 1
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.35