Yasunari Miyagi is an OB/Gyn doctor, Okayama city, Japan, since 2008, and a representative of Medical Data Labo, Okayama city, Japan, since 2017. He graduated from Okayama University Medical School and became a medical trainee at the Department of Obstetrics and Gynecology at Okayama University Hospital in 1985. He received his Ph.D. degree in 1993 from Okayama University. He was a visiting professor at the Department of Gynecologic Oncology at the Saitama Medical University International Medical Center, Saitama Prefecture, Japan, from 2019 to 2021. His areas of research interest are programmed statistical analysis, artificial intelligence, and laparoscopic surgery for benign gynecologic diseases. He possesses two patents in Japan regarding the system for prediction of blastocyst prognosis with artificial intelligence. He has memberships at the following academic societies: the Japanese Association for Medical Artificial Intelligence, the Japan Society of Obstetrics and Gynecology, the Japan Society of Gynecologic Oncology, the Japan Society of Clinical Oncology, the Japan Society for Endoscopic Surgery, the Japan Society of Gynecologic and Obstetric Endoscopy and Minimally Invasive Therapy, and the Japan Society for Reproductive Medicine.
Medical Data Labo
Okayama, Japan
High performance presentation
Japan Association of Obstetrics and Gynecology
Application of deep learning to the classification of uterine cervical squamous epithelial lesion from colposcopy images.
Best paper award
Japan Society for Reproductive Medicine
Feasibility of predicting live birth by combining conventional embryo evaluation with artificial intelligence applied to a blastocyst image in patients classified by age. Reprod Med Biol. 18(4):344–356, 2019.
2021 Yagi award
Chugoku Shikoku Society of Obstetrics and Gynecology
Application of deep learning to the classification of uterine cervical squamous epithelial lesion from colposcopy images.
Best presentation
Japan Association for Medical Artificial Intelligence
Recognition of fetal facial expressions of 4D ultrasound by AI