An artificial intelligence model integrating culprit lesion diagnosis and risk assessment for acute coronary syndrome
This work was supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project (2024ZD0521700), and the National Natural Science Foundation of China (No. 82441019 for L.J. Z.).
Authors
- Wen Huang (ORCID: https://orcid.org/0000-0001-7682-4354)
- Bin‐Jie Hu (ORCID: https://orcid.org/0000-0002-4716-4649)
- Zhi Xu (ORCID: https://orcid.org/0000-0002-1476-1367)
- Peng Xu (ORCID: https://orcid.org/0000-0002-5163-1529)
- Tong Yuan Liu
- Bangjun Guo (ORCID: https://orcid.org/0000-0002-5142-3252)
- Qian Chen (ORCID: https://orcid.org/0000-0002-5874-1317)
- Xin Wei Tao
- Fan Zhou (ORCID: https://orcid.org/0000-0003-4837-5955)
- Hong Qiao (ORCID: https://orcid.org/0000-0002-4360-5881)
- Chang Sheng Zhou (ORCID: https://orcid.org/0000-0003-1765-7669)
- Jia Ni Zou
- Xiangming Fang (ORCID: https://orcid.org/0000-0002-2283-1863)
Institutions
- Jiangnan University (CN)
- Boston Scientific (United States) (US)
- Second Affiliated Hospital of Nanjing Medical University (CN)
- Central Hospital of Wuhan (CN)
- Wuhan General Hospital of Guangzhou (CN)
- Siemens Healthcare (United States) (US)
- Wuxi People's Hospital (CN)
- Nanjing Medical University (CN)
Publication Details
- Journal
- EClinicalMedicine
- Published
- 2025-08-12
- DOI
- https://doi.org/10.1016/j.eclinm.2025.103415
- Citations
- 2
- Primary Topic
- Acute Myocardial Infarction Research
- Type
- article
- Field-Weighted Citation Impact
- 2.78
Funders
- National Natural Science Foundation of China
- Nanjing General Hospital of Nanjing Military Command