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Obstetrics & Gynecology Science|June 27, 2022
Depression in pregnant and postpartum women during COVID-19 pandemic: systematic review and meta-analysisNicholas Adrianto, Josephine Caesarlia, Fegita Beatrix Pajala
Obstetrics & Gynecology Science|June 27, 2022
Non-invasive continuous blood pressure monitoring using the ClearSight system for pregnant women at high risks of post-partum hemorrhage: comparison with invasive blood pressure monitoring during cesarean sectionTakuya Misugi, Takashi Juri, Koichi Suehiro, et al.
Obstetrics & Gynecology Science|September 15, 2020
Clinical experience of robotic myomectomy for fertility preservation using preoperative magnetic resonance imaging predictorSo Yun Park, Juhui Kim, Kyungah Jeong, et al.
Obstetrics & Gynecology Science|September 16, 2020
Minimally invasive search for a missing vibratorGreg J Marchand, Ali Azadi, Akarshi Kaue Brar, et al.
Obstetrics & Gynecology Science|October 16, 2020
Cervical polyp: evaluating the need of routine surgical intervention and its correlation with cervical smear cytology and endometrial pathology: a retrospective studyBhabani Pegu, Bheemanathi Hanuman Srinivas, Thangamuthu Sri Saranya, et al.
Obstetrics & Gynecology Science|October 5, 2020
A case of delivery of a pregnant woman with COVID-19 infection in Daegu, KoreaJin-Gon Bae, Jin-Kyeong Ha, Myoung Kwon, et al.
Obstetrics & Gynecology Science|June 16, 2022
A modified hydrostatic microfluidic pumpless device for in vitro murine ovarian tissue culture as research model for fertility preservationPaweena Thuwanut, Alongkorn Pimpin, Fueangrat Thatsanabunjong, et al.
Obstetrics & Gynecology Science|December 7, 2020
Comparison of single-port laparoscopy and laparotomy in early ovarian cancer surgical stagingKyu Hee Cho, Yeon Ju Lee, Kyung Jin Eoh, et al.
Obstetrics & Gynecology Science|December 7, 2020
Prenatal ultrasonographic findings of esophageal atresia: potential diagnostic role of the stomach shapeChi-Son Chang, Yunsun Choi, Seo-Yeon Kim, et al.
Obstetrics & Gynecology Science|December 29, 2020
The application of machine learning for predicting recurrence in patients with early-stage endometrial cancer: a pilot studyMunetoshi Akazawa, Kazunori Hashimoto, Katsuhiko Noda, et al.
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