学术论文

Artificial Intelligence-based Blastocyst and Split Embryo Evaluatiion System

December 2023

Interpretable Artificial Intelligence-Assisted Embryo Selection Improved Single-Blastocyst Transfer Outcomes: A Prospective Cohort Study

Reproductive BioMedicine Online
Link:https://doi.org/10.1016/j.rbmo.2023.103371
June 2025

Generalization validation of an interpretable artificial intelligence embryo selection model: a Cross-Brand retrospective study

Human Reproduction & The 41th Annual Meeting of the European Society of Human Reproduction and Embryology
Link:https://doi.org/10.1093/humrep/deaf097.404
July 2024

Utilizing Artificial Intelligence to Uncover Day 5 Morphokinetic Features Associated with Single Blastocyst Transfer Implantation Outcome

Human Reproduction & The 40th Annual Meeting of the European Society of Human Reproduction and Embryology
Link:https://doi.org/10.1093/humrep/deae108.517
June 2020

Automated Evaluation System Based on Artificial Intelligence and Visualization Technology Can Effectively Improve the Accuracy of Blastocyst Evaluation

The 36th Annual Meeting of the European Society of Human Reproduction and Embryology
Link:https://doi.org/10.1093/humrep/35.Supplement_1.1
January 2021

A Deep Learning Framework Design for Automatic Blastocyst Evaluation with Multifocal Images

IEEE Xplore
Link:https://ieeexplore.ieee.org/document/9328791
September 2023

An Interpretable Deep Learning-Based AI System for Predicting Blastocyst Formation from Early Embryo Development

Presentation at the 16th Annual Conference of the Chinese Society of Reproductive Medicine (CSRM)
November 2024

Internal and External Validation of an Interpretable Intelligent Blastocyst Evaluation System

Presentation at the 17th Annual Conference of the Chinese Society of Reproductive Medicine (CSRM)
November 2024

Practical Application of Trustworthy AI in Embryo Selection

Presentation at the 17th Annual Conference of the Chinese Society of Reproductive Medicine (CSRM)
June 2024

Automated Embryo Image Analysis: An Explainable AI Model Based on Day 5 Developmental Parameters for Predicting Clinical Pregnancy Outcomes of Blastocysts

Presentation at Jiangsu Provincial Conference on Reproductive Medicine