An opportunity for using artificial intelligence in modern gynecology
Introduction. Artificial intelligence (AI) is a technology that simulates human brain data processing, its intellectual behavior and critical thinking. Sophisticated AI models can potentially improve patient management by speeding up processes and increasing their accuracy and efficiency at a lower...
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| Format: | Article |
| Language: | Russian |
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IRBIS LLC
2024-09-01
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| Series: | Акушерство, гинекология и репродукция |
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| Online Access: | https://www.gynecology.su/jour/article/view/2029 |
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| author | Sh. L. Shailieva D. Kh. Mamchueva A. P. Vishnevskaya Kh. Sh. Dzhalaeva E. G. Ramazanova Y. R. Kokaeva Z. M. Eloeva D. R. Aisanova A. S. Vinogradova R. R. Tuko A. V. Sineva L. A. Valiullina A. A. Kutseva |
| author_facet | Sh. L. Shailieva D. Kh. Mamchueva A. P. Vishnevskaya Kh. Sh. Dzhalaeva E. G. Ramazanova Y. R. Kokaeva Z. M. Eloeva D. R. Aisanova A. S. Vinogradova R. R. Tuko A. V. Sineva L. A. Valiullina A. A. Kutseva |
| author_sort | Sh. L. Shailieva |
| collection | DOAJ |
| description | Introduction. Artificial intelligence (AI) is a technology that simulates human brain data processing, its intellectual behavior and critical thinking. Sophisticated AI models can potentially improve patient management by speeding up processes and increasing their accuracy and efficiency at a lower cost of human resources. Compared to other specialties, use of AI in gynecology remains in its infancy. It is important to understand that the available methods for clinical imaging have certain limitations, namely clinician's workload and data variably interpreted by different doctors. AI, in turn, has the potential to overcome these limitations while increasing diagnostic accuracy.Aim: to structure and analyze current published data on AI use in gynecology.Materials and Methods. A search for primary sources was carried out in the electronic databases PubMed, eLibrary and Google Scholar. The search queries included the following keywords "artificial intelligence", "gynecology", "endometrial cancer", "endometriosis", "ovarian cancer", "diagnostics", "oncogynecology" retrieved from February 2014 to February 2024. Articles were assessed according to PRISMA guidelines. After identification, before the screening stage, duplicates were excluded. At the screening stage, the titles and annotations of the identified articles were analyzed for eligibility to the review topic as well as for available full-text versions; abstracts and letters to the editorial board in scientific journals were excluded at this stage. 685 full-text articles were evaluated for eligibility, the inclusion criteria were as follows: publication in Russian or English; the study describes use of AI technologies in diagnostics or treatment of gynecological diseases. All disagreements between authors were resolved by consensus. Ultimately, 80 primary sources were included in this review.Results. AI-based systems have succeeded in image analyzing and interpreting and over the past decade have become powerful tools that have revolutionized the field of gynecological imaging. In the studies analyzed, AI was able to provide faster and more accurate forecasts and diagnostics, increasing the overall effectiveness of gynecological care. It is important to note that AI cannot fully replace doctors, but it can perfectly integrate into clinical practice, helping in the decision-making process and reducing errors in differential diagnosis and variability of interaction between different specialists. In the field of oncogynecology, undoubtedly one of the most promising aspects is the possibility of better and especially early diagnostics and, ultimately, improved patient survival.Conclusion. A great success has been achieved so far, and AI use is expected to extend in the next few years. In fact, it will take a very long way to go before AI-based technologies are fully integrated into clinical practice. |
| format | Article |
| id | doaj-art-b72d4fa0a9874b95935ad0131cae4acf |
| institution | Matheson Library |
| issn | 2313-7347 2500-3194 |
| language | Russian |
| publishDate | 2024-09-01 |
| publisher | IRBIS LLC |
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| series | Акушерство, гинекология и репродукция |
| spelling | doaj-art-b72d4fa0a9874b95935ad0131cae4acf2025-08-03T19:55:18ZrusIRBIS LLCАкушерство, гинекология и репродукция2313-73472500-31942024-09-0118456358010.17749/2313-7347/ob.gyn.rep.2024.511876An opportunity for using artificial intelligence in modern gynecologySh. L. Shailieva0D. Kh. Mamchueva1A. P. Vishnevskaya2Kh. Sh. Dzhalaeva3E. G. Ramazanova4Y. R. Kokaeva5Z. M. Eloeva6D. R. Aisanova7A. S. Vinogradova8R. R. Tuko9A. V. Sineva10L. A. Valiullina11A. A. Kutseva12North Caucasian State AcademyNorth Caucasian State AcademyDagestan State Medical University, Health Ministry of Russian FederationDagestan State Medical University, Health Ministry of Russian FederationDagestan State Medical University, Health Ministry of Russian FederationNorth Ossetian State Medical Academy, Health Ministry of Russian FederationNorth Ossetian State Medical Academy, Health Ministry of Russian FederationStavropol State Medical University, Health Ministry of Russian FederationStavropol State Medical University, Health Ministry of Russian FederationStavropol State Medical University, Health Ministry of Russian FederationBashkir State Medical University, Health Ministry of Russian FederationBashkir State Medical University, Health Ministry of Russian FederationPirogov Russian National Research Medical University, Health Ministry of Russian FederationIntroduction. Artificial intelligence (AI) is a technology that simulates human brain data processing, its intellectual behavior and critical thinking. Sophisticated AI models can potentially improve patient management by speeding up processes and increasing their accuracy and efficiency at a lower cost of human resources. Compared to other specialties, use of AI in gynecology remains in its infancy. It is important to understand that the available methods for clinical imaging have certain limitations, namely clinician's workload and data variably interpreted by different doctors. AI, in turn, has the potential to overcome these limitations while increasing diagnostic accuracy.Aim: to structure and analyze current published data on AI use in gynecology.Materials and Methods. A search for primary sources was carried out in the electronic databases PubMed, eLibrary and Google Scholar. The search queries included the following keywords "artificial intelligence", "gynecology", "endometrial cancer", "endometriosis", "ovarian cancer", "diagnostics", "oncogynecology" retrieved from February 2014 to February 2024. Articles were assessed according to PRISMA guidelines. After identification, before the screening stage, duplicates were excluded. At the screening stage, the titles and annotations of the identified articles were analyzed for eligibility to the review topic as well as for available full-text versions; abstracts and letters to the editorial board in scientific journals were excluded at this stage. 685 full-text articles were evaluated for eligibility, the inclusion criteria were as follows: publication in Russian or English; the study describes use of AI technologies in diagnostics or treatment of gynecological diseases. All disagreements between authors were resolved by consensus. Ultimately, 80 primary sources were included in this review.Results. AI-based systems have succeeded in image analyzing and interpreting and over the past decade have become powerful tools that have revolutionized the field of gynecological imaging. In the studies analyzed, AI was able to provide faster and more accurate forecasts and diagnostics, increasing the overall effectiveness of gynecological care. It is important to note that AI cannot fully replace doctors, but it can perfectly integrate into clinical practice, helping in the decision-making process and reducing errors in differential diagnosis and variability of interaction between different specialists. In the field of oncogynecology, undoubtedly one of the most promising aspects is the possibility of better and especially early diagnostics and, ultimately, improved patient survival.Conclusion. A great success has been achieved so far, and AI use is expected to extend in the next few years. In fact, it will take a very long way to go before AI-based technologies are fully integrated into clinical practice.https://www.gynecology.su/jour/article/view/2029artificial intelligenceaigynecologyendometrial cancerendometriosisovarian cancerdiagnosticsoncogynecology |
| spellingShingle | Sh. L. Shailieva D. Kh. Mamchueva A. P. Vishnevskaya Kh. Sh. Dzhalaeva E. G. Ramazanova Y. R. Kokaeva Z. M. Eloeva D. R. Aisanova A. S. Vinogradova R. R. Tuko A. V. Sineva L. A. Valiullina A. A. Kutseva An opportunity for using artificial intelligence in modern gynecology Акушерство, гинекология и репродукция artificial intelligence ai gynecology endometrial cancer endometriosis ovarian cancer diagnostics oncogynecology |
| title | An opportunity for using artificial intelligence in modern gynecology |
| title_full | An opportunity for using artificial intelligence in modern gynecology |
| title_fullStr | An opportunity for using artificial intelligence in modern gynecology |
| title_full_unstemmed | An opportunity for using artificial intelligence in modern gynecology |
| title_short | An opportunity for using artificial intelligence in modern gynecology |
| title_sort | opportunity for using artificial intelligence in modern gynecology |
| topic | artificial intelligence ai gynecology endometrial cancer endometriosis ovarian cancer diagnostics oncogynecology |
| url | https://www.gynecology.su/jour/article/view/2029 |
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