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Artificial Intelligence: The Future of Obstetrics and Gynecology

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Abstract

Background

Artificial intelligence or ‘big data’ comprises of algorithms which aid in decision making. It has made an impact on a number of professions including obstetrics and gynecology.

Objective

To make readers aware of where artificial intelligence has a role in obstetrics and gynecology.

Material and methods

A comprehensive review of the literature was undertaken to compile a list of instances where artificial intelligence was applied to obstetrics and gynecology.

Conclusion

Artificial intelligence should be utilized to benefit patient care and assist the physician in providing data for decision making.

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References

  1. Siristatidis C, Pouliakis A, Chrelias C, et al. Artificial intelligence in IVF: a need. Syst Biol Reprod Med. 2011;57(4):179–85.

    Article  PubMed  Google Scholar 

  2. Lutomski JE, Meaney S, Greene RA, et al. Expert systems for fetal assessment in labour. Cochrane Database Syst Rev. 2015;4:CD010708.

    Google Scholar 

  3. Jauniaux E, Prefumo F. Fetal heart monitoring in labour: from pinard to artificial intelligence. BJOG. 2016;123(6):870.

    Article  PubMed  CAS  Google Scholar 

  4. Guijarro-Berdiñas B, Alonso-Betanzos A. Empirical evaluation of a hybrid intelligent monitoring system using different measures of effectiveness. Artif Intell Med. 2002;24(1):71–96.

    Article  PubMed  Google Scholar 

  5. 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;20(16):10.

    Article  Google Scholar 

  6. Dawes GS, Moulden M, Redman CW. System 8000: computerized antenatal FHR analysis. J Perinat Med. 1991;19(1–2):47–51.

    Article  PubMed  CAS  Google Scholar 

  7. Elias KM, Fendler W, Stawiski K, et al. Diagnostic potential for a serum miRNA neural network for detection of ovarian cancer. Elife. 2017;6:1–28.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Idowu IO, Fergus P, Hussain A, et al. Artificial Intelligence for detecting preterm uterine activity in gynecology and obstetric care. In: 2015 IEEE international conference on computer and information technology.

  9. Fergus P, Cheung P, Hussain A, et al. Prediction of preterm deliveries from EHG signals using machine learning. PLoS ONE. 2013;8(10):e77154.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

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Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Seth GS Medical College and King Edward Memorial Hospital, Mumbai, India

    Gaurav Shyam Desai

Authors
  1. Gaurav Shyam Desai
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Correspondence to Gaurav Shyam Desai.

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The author declares that he has no conflict of interest.

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Additional information

Gaurav Shyam Desai MS, FCPS is an Assistant Professor of Obstetrics and Gynecology at the Seth GS Medical College and King Edward Memorial Hospital in Mumbai, India.

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Desai, G.S. Artificial Intelligence: The Future of Obstetrics and Gynecology. J Obstet Gynecol India 68, 326–327 (2018). https://doi.org/10.1007/s13224-018-1118-4

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  • DOI: https://doi.org/10.1007/s13224-018-1118-4

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