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Authors
Wong, Chinting
Yang, Qi
Liang, Yanting
Wei, Zhitao
Dai, Yi
Xu, Zeyan
Chen, Xiaobo
Du, Siyao
Han, Chu
Liang, Changhong
Zhang, Lina
Liu, Zaiyi
Wang, Ying
Shi, Zhenwei
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Funding
Funding for this research was provided by:
National Natural Science Foundation of China (82272059)
National Natural Science Foundation of China (62102103)
National Natural Science Foundation of China (82272088)
National Natural Science Foundation of China (82472062)
Noncommunicable Chronic Diseases-National Science and Technology Major Project (2024ZD0531100)
Noncommunicable Chronic Diseases-National Science and Technology Major Project (2024ZD0531100)
Noncommunicable Chronic Diseases-National Science and Technology Major Project (2024ZD0531100)
Natural Science Foundation for Distinguished Young Scholars of Guangdong Province (2023B1515020043)
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (2022B1212010011)
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (2022B1212010011)
Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (2022B1212010011)
Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (U22A20345)
Natural Science Foundation of Guangdong Province of China (2024A1515011672)
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Article History
Received: 24 June 2025
Accepted: 29 August 2025
First Online: 26 September 2025
Declarations
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: This study was approved by the institutional review boards of all participating hospitals. For the retrospective analysis, a waiver of informed consent was granted due to the use of de-identified data. The study adhered to the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) guidelines [].
: All authors agreed with the content of the present paper and consent to submit.
: The authors declare no competing interests.
