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Mingying Lai

As seen in: Nature, Frontiers in Physiology
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Articles

Association of cardiovascular-kidney-metabolic syndrome with blinding eye diseases: insights from a UK Biobank cohort analysis

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By Renyu Li, Jinqi Huang, Peng Huang, Meilin Chen, Jin Wang, Andong Huang, Jiapeng Wang, Kexin Chen, Xiaolin Gao, Haowen Liang, Yijun Deng, Yaqi Chen, Meiwen Tian, Honghua Yu, Mingying Lai, Kaiyi Chi, Yican Ying, Jiyun Hou
| Nature Verified
Abstract Cardiovascular-kidney-metabolic (CKM) syndrome’s overall impact on major blinding eye diseases remains unclear. We included participants from the UK Biobank. Baseline CKM syndrome at study entry was classified into five stages according to the American Heart Association criteria. We calculated the absolute incidence rates of cataract, glaucoma, and age-related macular degeneration (AMD) across CKM stages.
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Patient education for neuromyelitis optica spectrum disorder using large language models: combining expert assessment and real-world patient interaction

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By Chen Li, Yuting Hu, Xiaoyan Wang, Jiahao Ye, Shanshan Diao, Yanhui Xiao, Yingming Wang, Mingying Lai, Weihua Yang, Ruoyi Yao
| Frontiers in Physiology
Abstract Objectives: This study aimed to compare the educational performance of six mainstream LLMs for neuromyelitis optica spectrum disorder (NMOSD) and evaluated patient satisfaction during real-world interactions. Methods: This study was conducted from March to April 2026. In the first Phase, Twenty NMOSD-related questions derived from clinical guidelines and patient concerns were submitted to six LLMs (ChatGPT-5.4, Gemini-3.1-pro, Claude-4.6-Sonnet, DeepSeek-3.2, Kimi-2.5, and Qwen-3.5-plus).
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Artificial intelligence for pathologic myopia classification based on the META-PM system: a systematic review and meta-analysis

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By Yuting Hu, Xiaoyan Wang, Yuke Ji, Yuming Chen, Ziqi Liang, Sheng Wu, Weihua Yang, Mingying Lai
| Frontiers in Physiology
Abstract Background: Artificial intelligence (AI) has shown considerable potential for pathologic myopia (PM) detection, yet its overall diagnostic performance under the META-PM classification framework remains uncertain. Methods: A comprehensive literature search was conducted across PubMed, Web of Science, IEEE Xplore, and Embase up to February 10, 2026. Studies applying deep learning models for PM classification using the META-PM system were included.
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