نویسندگان
1 دانشجوی دکتری تخصصی، گروه مدیریت و فناوری اطلاعات سلامت، دانشکده مدیریت و اطلاعرسانی پزشکی، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران.
2 دانشیار، مرکز تحقیقات فناوری اطلاعات سلامت، دانشگاه علوم پزشکی اصفهان، اصفهان، ایران.
چکیده
کلیدواژهها
عنوان مقاله [English]
نویسندگان [English]
Introduction: Obstetrics and Gynecology is a sensitive field of medicine that requires high accuracy and speed of action. Artificial intelligence in the field of obstetrics and gynecology helps doctors diagnose diseases more accurately, predict pregnancy complications, and improve the delivery process by analyzing big medical data, ultrasound images, and patient data. This study aims to investigate the role and applications of artificial intelligence in the field of obstetrics and gynecology.
Methods: The methodology section should outline the key steps taken to conduct the study or research that forms the basis of this paper. This may include details on the study design, data collection procedures, participant recruitment, and analytical techniques employed. This study was conducted as a narrative review. To collect data, a systematic search was conducted in reputable scientific databases including PubMed, Scopus, ScienceDirect, Web of Science, and Google Scholar.
The keywords used in the search included combinations of the following terms:
“Artificial Intelligence”, “Machine Learning”, “Deep Learning”, “Obstetrics”, “Gynecology”, “Maternal Health”, “Prenatal Care”, “Medical Imaging”, and “Clinical Decision Support Systems”.
The search time frame was considered between 2014 and 2025 to focus on up-to-date studies. Articles were selected after reviewing the title, abstract, and full text based on inclusion and exclusion criteria. The inclusion criteria included research articles, reviews, case reports, and review studies published in English with a focus on the application of AI in obstetrics and gynecology. Articles that were not directly related to the topic, were unpublished, or were in other languages were excluded.
Finally, 40 articles with the highest relevance and scientific quality were selected for analysis. Data analysis was conducted qualitatively and thematically to identify the main areas of application, benefits, challenges, and future research of AI in this field.
Results
Important applications of AI in obstetrics and gynecology:
Diagnosis of fetal diseases and abnormalities:
By processing ultrasound images, AI can help identify fetal abnormalities such as Down syndrome and heart problems.
Prediction of pregnancy complications:
Machine learning algorithms can predict the risk of gestational diabetes, preeclampsia, and premature birth with high accuracy.
Assisted childbirth:
Smart systems can monitor the labor process and predict whether medical intervention is needed.
Postpartum hemorrhage management:
By analyzing clinical data, AI can identify the risk of bleeding and enable timely management.
Challenges and considerations, including patient privacy, data quality, and the need to train medical professionals to use AI, are among the obstacles to the expansion of this technology in obstetrics and gynecology.
Conclusion: By providing accurate and fast tools, AI can revolutionize obstetrics and gynecology and improve maternal and newborn health. As technology advances and access to data increases, AI applications in this field are expected to become more widespread and effective.
کلیدواژهها [English]
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