1. Iftikhar P, Kuijpers MV, Khayyat A, Iftikhar A, DeGouvia De Sa M. Artificial Intelligence: A New Paradigm in Obstetrics and Gynecology Research and Clinical Practice. Cureus. 2020;12(2):e7124.
2. Desai GS. Artificial Intelligence: The Future of Obstetrics and Gynecology. J Obstet Gynaecol India. 2018;68(4):326-327. doi:10.1007/s13224-018-1118-4
3. Beam AL, Kohane IS. Big Data and Machine Learning in Health Care. JAMA. 2018;319(13):1317-1318. doi:10.1001/jama.2017.18391
4. Brocklehurst P; INFANT Collaborative Group. A study of an intelligent system to support decision making in the management of labour using the cardiotocograph - the INFANT study protocol. BMC Pregnancy Childbirth. 2016;16:10.
5. Makary MA, Daniel M. Medical error-the third leading cause of death in the US. BMJ. 2016;353:i2139.
6. Samavedam S. Medicolegal Aspects of Obstetric Critical Care. Indian J Crit Care Med. 2021;25(Suppl 3):S279-S282. doi:10.5005/jp-journals-10071-24069
7. Williams P, Murchie P, Bond C. Patient and primary care delays in the diagnostic pathway of gynaecological cancers: a systematic review of influencing factors. Br J Gen Pract. 2019;69(679):e106-e111. doi:10.3399/bjgp19X700781
8. Amant F, Mirza MR, Koskas M, Creutzberg CL. Cancer of the corpus uteri. Int J Gynaecol Obstet. 2018;143 Suppl 2:37-50. doi:10.1002/ijgo.12612
9. Liu L, Jiao Y, Li X, Ouyang Y, Shi D. Machine learning algorithms to predict early pregnancy loss after in vitro fertilization-embryo transfer with fetal heart rate as a strong predictor. Comput Methods Programs Biomed. 2020;196:105624. doi:10.1016/j.cmpb.2020.105624
10. Bhattad PB, Jain V. Artificial Intelligence in Modern Medicine - The Evolving Necessity of the Present and Role in Transforming the Future of Medical Care. Cureus. 2020;12(5):e8041.
11. Drukker L, Noble JA, Papageorghiou AT. Introduction to artificial intelligence in ultrasound imaging in obstetrics and gynecology. Ultrasound Obstet Gynecol. 2020;56(4):498-505. doi:10.1002/uog.22122
12. Wang R, Pan W, Jin L, et al. Artificial intelligence in reproductive medicine. Reproduction. 2019;158(4):R139-R154. doi:10.1530/REP-18-0523
13. Emin EI, Emin E, Papalois A, Willmott F, Clarke S, Sideris M. Artificial Intelligence in Obstetrics and Gynaecology: Is This the Way Forward?. In Vivo. 2019;33(5):1547-1551. doi:10.21873/invivo.11635
14. Kim YH. Artificial intelligence in medical ultrasonography: driving on an unpaved road. Ultrasonography. 2021;40(3):313-317. doi:10.14366/usg.21031
15. Wu L, Wei D, Yang N, Lei H, Wang Y. Artificial Intelligence Algorithm-Based Analysis of Ultrasonic Imaging Features for Diagnosis of Pregnancy Complicated with Brain Tumor [retracted in: J Healthc Eng. 2023 Oct 11;2023:9798341.
16. Wu Y, Shen Y, Sun H. Intelligent Algorithm-Based Analysis on Ultrasound Image Characteristics of Patients with Lower Extremity Arteriosclerosis Occlusion and Its Correlation with Diabetic Mellitus Foot. J Healthc Eng. 2021;2021:7758206.
17. Gupta K, Balyan K, Lamba B, Puri M, Sengupta D, Kumar M. Ultrasound placental image texture analysis using artificial intelligence to predict hypertension in pregnancy. J Matern Fetal Neonatal Med. 2022;35(25):5587-5594. doi:10.1080/14767058.2021.1887847
18. Murillo-Llorente MT, Fajardo-Montañana C, Perez-Bermejo M. Artificial Neural Network for Predicting Iodine Deficiency in the First Trimester of Pregnancy in Healthy Women. Tohoku J Exp Med. 2020;252(3):185-191. doi:10.1620/tjem.252.185
19. Burgos-Artizzu XP, Coronado-Gutiérrez D, Valenzuela-Alcaraz B, et al. Analysis of maturation features in fetal brain ultrasound via artificial intelligence for the estimation of gestational age. Am J Obstet Gynecol MFM. 2021;3(6):100462. doi:10.1016/j.ajogmf.2021.100462
20. Sakai A, Komatsu M, Komatsu R, et al. Medical Professional Enhancement Using Explainable Artificial Intelligence in Fetal Cardiac Ultrasound Screening. Biomedicines. 2022;10(3):551.
21. Lin M, He X, Guo H, et al. Use of real-time artificial intelligence in detection of abnormal image patterns in standard sonographic reference planes in screening for fetal intracranial malformations. Ultrasound Obstet Gynecol. 2022;59(3):304-316. doi:10.1002/uog.24843
22. Sun Q, Zou X, Yan Y, et al. Machine Learning-Based Prediction Model of Preterm Birth Using Electronic Health Record. J Healthc Eng. 2022;2022:9635526.
23. Zaninovic N, Rosenwaks Z. Artificial intelligence in human in vitro fertilization and embryology. Fertil Steril. 2020;114(5):914-920. doi:10.1016/j.fertnstert.2020.09.157
24. Yin P, Wang H. Evaluation of Nursing Effect of Pelvic Floor Rehabilitation Training on Pelvic Organ Prolapse in Postpartum Pregnant Women under Ultrasound Imaging with Artificial Intelligence Algorithm. Comput Math Methods Med. 2022;2022:1786994.
25. Goodday SM, Karlin E, Brooks A, et al. Better Understanding of the Metamorphosis of Pregnancy (BUMP): protocol for a digital feasibility study in women from preconception to postpartum. NPJ Digit Med. 2022;5(1):40.
26. Pergialiotis V, Pouliakis A, Parthenis C, et al. The utility of artificial neural networks and classification and regression trees for the prediction of endometrial cancer in postmenopausal women. Public Health. 2018;164:1-6. doi:10.1016/j.puhe.2018.07.012