Article Versions Notes

Hu Y, Meng Y, Liang Y, Zhang Y, Chen B, Qiu J, Meng Z, Luo J. Machine Learning and Optical-Coherence-Tomography-Derived Radiomics Analysis to Predict the Postoperative Anatomical Outcome of Full-Thickness Macular Hole. Bioengineering. 2024; 11(9):949. https://doi.org/10.3390/bioengineering11090949

Hu, Yuqian, Yongan Meng, Youling Liang, Yiwei Zhang, Biying Chen, Jianing Qiu, Zhishang Meng, and Jing Luo. 2024. "Machine Learning and Optical-Coherence-Tomography-Derived Radiomics Analysis to Predict the Postoperative Anatomical Outcome of Full-Thickness Macular Hole" Bioengineering 11, no. 9: 949. https://doi.org/10.3390/bioengineering11090949

Hu, Y., Meng, Y., Liang, Y., Zhang, Y., Chen, B., Qiu, J., Meng, Z., & Luo, J. (2024). Machine Learning and Optical-Coherence-Tomography-Derived Radiomics Analysis to Predict the Postoperative Anatomical Outcome of Full-Thickness Macular Hole. Bioengineering, 11(9), 949. https://doi.org/10.3390/bioengineering11090949