This paper is in the following e-collection/theme issue:

Digital Health Reviews (1289) Artificial Intelligence (1371) Obstetrics, Gynecology, and Reproductive Medicine (225)

Published on in Vol 24, No 4 (2022): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/35465, first published .
Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review

Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review

Contributions of Artificial Intelligence Reported in Obstetrics and Gynecology Journals: Systematic Review

Authors of this article:

Ferdinand Dhombres1, 2 Author Orcid Image ;   Jules Bonnard3 Author Orcid Image ;   Kévin Bailly3 Author Orcid Image ;   Paul Maurice1 Author Orcid Image ;   Aris T Papageorghiou4 Author Orcid Image ;   Jean-Marie Jouannic1, 2 Author Orcid Image
Article Authors Cited by (32) Tweetations (6) Metrics

Journals

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  2. Du Y, McNestry C, Wei L, Antoniadi A, McAuliffe F, Mooney C. Machine learning-based clinical decision support systems for pregnancy care: A systematic review. International Journal of Medical Informatics 2023;173:105040 View
  3. Weichert J, Diedrich K, Gembruch U. Künstliche Intelligenz in der Gynäkologie und Geburtshilfe. Die Gynäkologie 2022;55(10):717 View
  4. Papastefanou I, Nicolaides K, Salomon L. Audit of fetal biometry: understanding sources of error to improve our practice. Ultrasound in Obstetrics & Gynecology 2023;61(4):431 View
  5. Chavez M, Butler T, Rekawek P, Heo H, Kinzler W. Chat Generative Pre-trained Transformer: why we should embrace this technology. American Journal of Obstetrics and Gynecology 2023;228(6):706 View
  6. Ziganshin A, Dikke G, Mudrov V. Predicting a clinically narrow pelvis using neural network data analysis. Obstetrics, Gynecology and Reproduction 2023;17(2):211 View
  7. Arain Z, Iliodromiti S, Slabaugh G, David A, Chowdhury T. Machine learning and disease prediction in obstetrics. Current Research in Physiology 2023;6:100099 View
  8. Czabanski R, Jezewski M, Leski J, Horoba K, Wrobel J, Martinek R, Barnova K. Refining the rule base of fuzzy classifier to support the evaluation of fetal condition. Applied Soft Computing 2023;147:110790 View
  9. Fischer A, Rietveld A, Teunissen P, Hoogendoorn M, Bakker P. What is the future of artificial intelligence in obstetrics? A qualitative study among healthcare professionals. BMJ Open 2023;13(10):e076017 View
  10. Suhag A, Kidd J, McGath M, Rajesh R, Gelfinbein J, Cacace N, Monteleone B, Chavez M. ChatGPT: a pioneering approach to complex prenatal differential diagnosis. American Journal of Obstetrics & Gynecology MFM 2023;5(8):101029 View
  11. Jost E, Kosian P, Jimenez Cruz J, Albarqouni S, Gembruch U, Strizek B, Recker F. Evolving the Era of 5D Ultrasound? A Systematic Literature Review on the Applications for Artificial Intelligence Ultrasound Imaging in Obstetrics and Gynecology. Journal of Clinical Medicine 2023;12(21):6833 View
  12. Yeh J, Clare C. Women’s Health and Artificial Intelligence (AI): Addressing Potential for Bias and Discrimination in AI. Current Women s Health Reviews 2023;19(4) View
  13. Deslandes A, Avery J, Chen H, Leonardi M, Condous G, Hull M. Artificial intelligence as a teaching tool for gynaecological ultrasound: A systematic search and scoping review. Australasian Journal of Ultrasound in Medicine 2024;27(1):5 View
  14. Medjedovic E, Stanojevic M, Jonuzovic-Prosic S, Ribic E, Begic Z, Cerovac A, Badnjevic A. Artificial intelligence as a new answer to old challenges in maternal-fetal medicine and obstetrics. Technology and Health Care 2024;32(3):1273 View
  15. Zhao T, Gao Y, Zhan W, Sun H, Zhang T, Li L, Zuo W, Tang X, Li Y, Tian Y. Municipal solid waste (MSW) under the population shrinking and aging: Spatio-temporal patterns, driving forces, and the impact of smart city development. Journal of Cleaner Production 2024;434:140124 View
  16. Gong L, Tang Y, Xie H, Zhang L, Sun Y. Predicting cervical intraepithelial neoplasia and determining the follow-up period in high-risk human papillomavirus patients. Frontiers in Oncology 2024;13 View
  17. Brandão M, Mendes F, Martins M, Cardoso P, Macedo G, Mascarenhas T, Mascarenhas Saraiva M. Revolutionizing Women’s Health: A Comprehensive Review of Artificial Intelligence Advancements in Gynecology. Journal of Clinical Medicine 2024;13(4):1061 View
  18. Wu Z, Yu X, Wang F, Xu C. Application of artificial intelligence in dental implant prognosis: A scoping review. Journal of Dentistry 2024;144:104924 View
  19. Peled T, Sela H, Weiss A, Grisaru‐Granovsky S, Agrawal S, Rottenstreich M. Evaluating the validity of ChatGPT responses on common obstetric issues: Potential clinical applications and implications. International Journal of Gynecology & Obstetrics 2024;166(3):1127 View
  20. Lourenço M, Arrufat T, Satorres E, Maderuelo S, Novillo-Del Álamo B, Guerriero S, Orozco R, Alcázar J. Ultrasound-Based Deep Learning Models Performance versus Expert Subjective Assessment for Discriminating Adnexal Masses: A Head-to-Head Systematic Review and Meta-Analysis. Applied Sciences 2024;14(7):2998 View
  21. Bernardes L, Fernandes A, Carvalho M, Ottolia J, Hamani M, Oliveira I, Kubota G, da Silva V, Veloso A, de Carvalho M, de Amorim Filho A, Arenholt L, Leutscher P, de Andrade D. Assessment of Human Fetuses Undergoing Acute Pain: Validation of the Fetal-7 Scale. The Journal of Pain 2024;25(9):104527 View
  22. Boie S, Glavind J, Bor P, Steer P, Riis A, Thiesson B, Uldbjerg N. Continued versus discontinued oxytocin stimulation in the active phase of labour (CONDISOX): individual management based on artificial intelligence - a secondary analysis. BMC Pregnancy and Childbirth 2024;24(1) View
  23. Shara N, Mirabal-Beltran R, Talmadge B, Falah N, Ahmad M, Dempers R, Crovatt S, Eisenberg S, Anderson K. Use of Machine Learning for Early Detection of Maternal Cardiovascular Conditions: Retrospective Study Using Electronic Health Record Data. JMIR Cardio 2024;8:e53091 View
  24. Wahbah M, Zitouni M, Al Sakaji R, Funamoto K, Widatalla N, Krishnan A, Kimura Y, Khandoker A. A deep learning framework for noninvasive fetal ECG signal extraction. Frontiers in Physiology 2024;15 View
  25. Yaseen I, Rather R. A Theoretical Exploration of Artificial Intelligence’s Impact on Feto-Maternal Health from Conception to Delivery. International Journal of Women's Health 2024;Volume 16:903 View
  26. Sinha R, Raina R, Bag M, Rupa B. Empowering gynaecologists with Artificial Intelligence: Tailoring surgical solutions for fibroids. European Journal of Obstetrics & Gynecology and Reproductive Biology 2024;299:72 View
  27. Pinheiro Y, Silva R. Artificial intelligence in gynecology and obstetrics: from the enthusiasm of use in practice to the challenges of implementation. Revista Brasileira de Ginecologia e Obstetrícia 2024;46 View
  28. Haj Yahya R, Roman A, Grant S, Whitehead C. Antenatal screening for fetal structural anomalies – Routine or targeted practice?. Best Practice & Research Clinical Obstetrics & Gynaecology 2024;96:102521 View
  29. Patel D, Chaudhari K, Acharya N, Shrivastava D, Muneeba S. Artificial Intelligence in Obstetrics and Gynecology: Transforming Care and Outcomes. Cureus 2024 View
  30. Lin X, Liang C, Liu J, Lyu T, Ghumman N, Campbell B. Artificial Intelligence–Augmented Clinical Decision Support Systems for Pregnancy Care: Systematic Review. Journal of Medical Internet Research 2024;26:e54737 View
  31. Silva C, Nascimento D, Dantas G, Fonseca K, Hespanhol L, Rego A, Araújo-Filho I. Impact of artificial intelligence on the training of general surgeons of the future: a scoping review of the advances and challenges. Acta Cirúrgica Brasileira 2024;39 View
  32. Weichert J, Scharf J. Advancements in Artificial Intelligence for Fetal Neurosonography: A Comprehensive Review. Journal of Clinical Medicine 2024;13(18):5626 View