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Review
. 2025 Feb 10;18(1):20.
doi: 10.1186/s12245-025-00820-8.

Artificial intelligence in gynecologic and obstetric emergencies

Hassan M Elbiss  1 , Fikri M Abu-Zidan  2
Affiliations
Review

Artificial intelligence in gynecologic and obstetric emergencies

Hassan M Elbiss et al. Int J Emerg Med. .

Abstract
in English, German

Background: Artificial intelligence (AI) uses a process by which machines perform human-like functions such as automated clinical decisions. This may operate efficiently in gynecologic and obstetric emergencies. We aimed to review the role and applications of AI in gynecologic and obstetric emergencies.

Methods: A literature search was carried out in November 2023 in PubMed, Cochrane Library and Google Scholar using the keywords combination of "artificial intelligence, gynecology and obstetrics". Relevant articles were selected and read. Reference lists of the selected articles were also searched.

Results: The literature demonstrated the role of AI to improve healthcare in emergency settings in several aspects such as diagnostic imaging, improving predictions in emergencies, and improving planning and resource allocation for emergency services. AI works objectively, overcoming human biases in decision-making. Creating interconnected data registries for AI will likely enhance its performance. Validation research in emergency settings has shown that AI-prediction tools perform more accurately compared with the estimation of risk and outcomes by gynecologists and obstetricians in emergency situations including endometriosis and acute abdominal pain. There was acceptance of AI and its potential benefits. Ethical dilemmas of using AI include data governance, responsibility for errors, and security issues. Providing training on AI to healthcare professionals working in emergency departments is needed.

Conclusions: Healthcare professionals should educate themselves about the anticipated role of AI in gynecologic and obstetric emergencies, its indications, limitations, and ethical considerations so that they can take steps towards its application in their future practice using defined guidelines.

WHY IS THIS REVIEW IS IMPORTANT?: The use of AI in healthcare has created polarized thoughts among emergency medicine professionals. This review is an effort to compare the pros and cons of using AI in gynecologic and obstetric emergencies so that AI can be properly applied in these specialities. WHAT DOES THIS REVIEW SHOW?: This review shows that there are several research studies in gynecology and obstetrics emergencies with positive points in favor of using AI in emergencies like acute abdominal and pelvic pain, and endometriosis. There are some reservations from the practitioners to use it due to lack of understanding of its nature, advantages and limitations. By narrating the findings of AI-related publications in gynecology and obstetrics emergency, we propose their applications and their limitations. WHAT ARE THE KEY FINDINGS?: AI can help in critical decision-making in emergency gynecologic and obstetric situations under the conditions of correct input information and human supervision. So, AI can assist gynecologists in deciding which treatment approach to use in emergencies and it may also reduce the burden on human professionals and save time by prompt interventional decisions. HOW IS PATIENT CARE IMPACTED?: Using AI with the input of trained medical professionals and software engineers, decision-making in gynecologic and obstetric emergencies can be made more efficient. AI-assisted tools can predict the outcomes of patients rapidly, saving time and avoiding delays in directing further care.

Keywords: Artificial intelligence; Emergency; Gynecology; Obstetrics.

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Conflict of interest statement

Declarations. Ethical approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
The DIKW pyramid consists of four components: data, information, knowledge, and wisdom, that develop overtime from base to top (Illustrated by Professor Fikri Abu-Zidan, The Research Office, College of Medicine and Health Sciences, United Arab Emirates University)
Fig. 2
Fig. 2
PubMed Search result of the term “artificial intelligence” for the period of 1951 to 2023 shows its dramatic exponential growth. There was less than 10 annual articles before 1971 while it reached more than 37 000 articles in year 2023 (Illustrated by Professor Fikri Abu-Zidan, The Research Office, College of Medicine and Health Sciences, United Arab Emirates University)
Fig. 3
Fig. 3
Artificial neural networks, which mimick human neuron networks, have at least three layers: (1) input layer, (2) hidden layer, and (3) output layer. Each neuron of a layer is connected with every neuron of the following layer but not with the neurons of the same layer (Illustrated by Professor Fikri Abu-Zidan, The Research Office, College of Medicine and Health Sciences, United Arab Emirates University)
Fig. 4
Fig. 4
The Gartner Hype Cycle methodology describes how the perceived value of a given technology evolves. Reproduced from De Simone B et al. Knowledge, attitude, and practice of artificial intelligence in emergency and trauma surgery, the ARIES project: an international web-based survey. World J Emerg Surg. 2022;17:10 which is distributed under the terms of the Creative Commons Attribution 4.0 International License
See this image and copyright information in PMC

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