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Cited by in CrossRef
For: Miyagi Y, Habara T, Hirata R, Hayashi N. Predicting a live birth by artificial intelligence incorporating both the blastocyst image and conventional embryo evaluation parameters. Artif Intell Med Imaging 2020; 1(3): 94-107 [DOI: 10.35711/aimi.v1.i3.94]
URL: https://www.wjgnet.com/2644-3260/full/v1/i3/94.htm
Number Citing Articles
1
Jerónimo Hernández-González, Olga Valls, Adrián Torres-Martín, Jesús Cerquides. Modeling three sources of uncertainty in assisted reproductive technologies with probabilistic graphical modelsComputers in Biology and Medicine 2022; 150: 106160 doi: 10.1016/j.compbiomed.2022.106160
2
Nina Dissler, Daniela Nogueira, Bertrand Keppi, Pierre Sanguinet, Christophe Ozanon, Cendrine Geoffroy-Siraudin, Xavier Pollet-Villard, Alexandra Boussommier-Calleja. Artificial intelligence-powered assisted ranking of sibling embryos to increase first cycle pregnancy rateReproductive BioMedicine Online 2024; 49(1): 103887 doi: 10.1016/j.rbmo.2024.103887
3
Hang Liu, Zhuoran Zhang, Yifan Gu, Changsheng Dai, Guanqiao Shan, Haocong Song, Daniel Li, Wenyuan Chen, Ge Lin, Yu Sun. Development and evaluation of a live birth prediction model for evaluating human blastocysts from a retrospective studyeLife 2023; 12 doi: 10.7554/eLife.83662
4
Yasunari Miyagi, Toshiyuki Hata, Saori Bouno, Aya Koyanagi, Takahito Miyake. Recognition of facial expression of fetuses by artificial intelligence (AI)Journal of Perinatal Medicine 2021; 49(5): 596 doi: 10.1515/jpm-2020-0537
5
Shanshan Wang, Lei Chen, Haixiang Sun. Interpretable artificial intelligence-assisted embryo selection improved single-blastocyst transfer outcomes: a prospective cohort studyReproductive BioMedicine Online 2023; 47(6): 103371 doi: 10.1016/j.rbmo.2023.103371
6
Yulia Michailov, Shevach Friedler, Bozhena Saar-Ryss. Methods to improve frozen-thawed blastocyst transfer outcomes- the IVF laboratory perspectiveJournal of IVF-Worldwide 2023; 1(1-3) doi: 10.46989/001c.87541
7
Yasunari Miyagi, Yasuyuki Mio, Keitaro Yumoto, Rei Hirata, Toshihiro Habara, Nobuyoshi Hayashi. Kinetic Energy and the Free Energy Principle in the Birth of Human LifeReproductive Medicine 2024; 5(2): 65 doi: 10.3390/reprodmed5020008
8
Yasunari Miyagi, Toshihiro Habara, Rei Hirata, Nobuyoshi Hayashi. Predicting implantation by using dual AI system incorporating three‐dimensional blastocyst image and conventional embryo evaluation parameters—A pilot studyReproductive Medicine and Biology 2024; 23(1) doi: 10.1002/rmb2.12612
9
Mikkel Fly Kragh, Henrik Karstoft. Embryo selection with artificial intelligence: how to evaluate and compare methods?Journal of Assisted Reproduction and Genetics 2021; 38(7): 1675 doi: 10.1007/s10815-021-02254-6
10
Toshiyuki Hata, Yasunari Miyagi. Recognition of Fetal Facial Expressions Using Artificial Intelligence Deep LearningDonald School Journal of Ultrasound in Obstetrics and Gynecology 2021; 15(3): 223 doi: 10.5005/jp-journals-10009-1710
11
R. Barkavi, G. Yamuna, C. Jayaram. Proceedings of International Conference on Communication and Computational TechnologiesAlgorithms for Intelligent Systems 2023; : 947 doi: 10.1007/978-981-99-3485-0_76
12
Aşina Bayram, Ibrahim Elkhatib, Erkan Kalafat, Andrea Abdala, Virginia Ferracuti, Laura Melado, Barbara Lawrenz, Human Fatemi, Daniela Nogueira. Steady morphokinetic progression is an independent predictor of live birth: a descriptive reference for euploid embryosHuman Reproduction Open 2024; 2024(4) doi: 10.1093/hropen/hoae059
13
Sergei Sergeev, Iuliia Diakova, Lasha Nadirashvili. Neural networks pipeline for quality management in IVF laboratoryJournal of IVF-Worldwide 2024; 2(4) doi: 10.46989/001c.124947