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Authors
Zhao, Jianxin
Tang, Yao
Li, Shengli
Wang, Ke
Tao, Jing
Chen, Chunyi
Zhou, Jiayuan
Cui, Lang
Wang, Yuji
Huang, Cheng
Liu, Zheng
Kang, Hong
Zhu, Jun
Huang, Yong
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Funding
Funding for this research was provided by:
National Key Research and Development Program of China (2022YFC2704701)
National Key Research and Development Program of China (2024YFC2707000)
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Article History
Received: 27 November 2025
Accepted: 2 March 2026
First Online: 6 March 2026
Declarations
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: The study was approved by the Ethics Committee of West China Second University Hospital (No. 2019YFS0530). The requirement for informed consent was waived because this study used routinely collected clinical ultrasound data that were automatically anonymised upon upload to the AI-QC platform, with all personal identifiers removed. The research analysed only AI-generated quality scores and structured assessment outputs and did not involve manual review of identifiable ultrasound images. No additional procedures or interventions were introduced. The ethics committee determined that the study involved minimal risk to participants and therefore did not require individual informed consent.
: Not applicable.
: Shengli Li has led the development and prior validation of the AI-based fetal ultrasound quality control system evaluated in this study, which may be perceived as an intellectual competing interest. All other authors declare no competing interests.
