基于人工智能的Day 5新形态学参数预测单囊胚移植结果
Human Reproduction & The 40th Annual Meeting of the … 阅读更多
胚胎图像的自动分析：基于Day5可解释发育参数的人工智能模型预测囊胚的临床妊娠结局
江苏省生殖医学会议发言
Interpretable Artificial Intelligence-Assisted Embryo Selection Improved Single-Blastocyst Transfer Outcomes: A Prospective Cohort Study
This prospective cohort study demonstrates that an interpretable AI model may assist embryologists in improving implantation rates during single-blastocyst transfer. The findings support the potential clinical value of AI-assisted embryo selection, warranting further validation in broader settings.
可解释的人工智能辅助胚胎选择改善了单囊胚移植结果：一项前瞻性队列研究
Reproductive BioMedicine Online
基于可解释深度学习模型建立早期胚胎预测囊胚发育结局的新型AI预测系统
中华医学会第十六次全国生殖医学学术会议发言
A Deep Learning Framework Design for Automatic Blastocyst Evaluation with Multifocal Images
A deep learning framework was developed to assess blastocyst quality from multifocal images, with a multichannel VGG-16 model enabling accurate and objective morphological analysis.
一个基于深度学习自动评估多焦距囊胚图像的框架设计
IEEE Xplore