Hepatic Steatosis Analysis in Metabolic Dysfunction-Associated Steatotic Liver Disease Based on Artificial Intelligence
AI recognition technology may be a new tool for the accurate diagnosis of steatosis in MASLD, providing a more precise and objective method for evaluating steatosis in preclinical murine MASLD models under various experimental and treatment conditions.
Authors
- Yandi Xie (ORCID: https://orcid.org/0000-0001-5002-341X)
- Rui Jin (ORCID: https://orcid.org/0000-0003-4544-6535)
- Xiaoxiao Wang (ORCID: https://orcid.org/0000-0003-4764-2281)
- Zilong Wang (ORCID: https://orcid.org/0000-0001-8700-8299)
- Fangfang Liu (ORCID: https://orcid.org/0000-0003-1059-8598)
- Feng Liu (ORCID: https://orcid.org/0000-0002-0316-4938)
- Qiang Yang (ORCID: https://orcid.org/0000-0001-5059-8360)
- Nan Wu (ORCID: https://orcid.org/0000-0002-9939-9810)
- Xiaohe Li (ORCID: https://orcid.org/0000-0003-4315-5953)
- Yi Song (ORCID: https://orcid.org/0000-0001-6990-6781)
- Xiao Teng
- Hui-Ying Rao
Institutions
- Peking University (CN)
- Zhejiang Zanyu Technology (China) (CN)
- Peking University People's Hospital (CN)
- Histoindex (Singapore) (SG)
Publication Details
- Journal
- Diagnostics
- Published
- 2024-12-23
- DOI
- https://doi.org/10.3390/diagnostics14242889
- Citations
- 5
- Primary Topic
- Liver Disease Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.93
Funders
- National Natural Science Foundation of China
- National Key Research and Development Program of China