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:: Volume 14, Issue 3 (Summer 2023) ::
Caspian J Intern Med 2023, 14(3): 526-533 Back to browse issues page
Endometrial cancer in women with abnormal uterine bleeding: Data mining classification methods
Farah Farzaneh , Azadeh Jafari Ashtiani , Mohammad Mohammad Hashemi , Maryam Sadat Hosseini , Maliheh Arab , Tahereh Ashrafganjoei , Shaghayegh Hooshmand Chayjan
Preventative Gynecology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran , azade.jafari@gmail.com
Abstract:   (901 Views)
Background: Over the last decade, artificial intelligence in medicine has been growing. Since endometrial cancer can be treated with early diagnosis, finding a non-invasive method for screening patients, especially high-risk ones, could have a particular value. Regarding the importance of this issue, we aimed to investigate the risk factors related to endometrial cancer and find a tool to predict it using machine learning.
Methods: In this cross-sectional study, 972 patients with abnormal uterine bleeding from January 2016 to January 2021 were studied, and the essential characteristics of each patient, along with the findings of curettage pathology, were analyzed using statistical methods and machine learning algorithms, including artificial neural networks, classification and regression trees, support vector machine, and logistic regression.
Results: Out of 972 patients with a mean age of 45.77 ± 10.70 years, 920 patients had benign pathology, and 52 patients had endometrial cancer. In terms of endometrial cancer prediction, the logistic regression model had the best performance (sensitivity of 100% and 98%, specificity of 98.83% and 98.7%, for trained and test data sets respectively,) followed by the classification and regression trees model.
Conclusion: Based on the results, artificial intelligence-based algorithms can be applied as a non-invasive screening method for predicting endometrial cancer.

 
Keywords: Endometrial Cancer, Artificial Intelligence, Machine Learning
Full-Text [PDF 434 kb]   (507 Downloads)    
Type of Study: Original Article | Subject: Obstetrics & Gynicology
Received: 2022/06/16 | Accepted: 2022/08/14 | Published: 2023/05/9
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Farzaneh F, Jafari Ashtiani A, Hashemi M M, Hosseini M S, Arab M, Ashrafganjoei T et al . Endometrial cancer in women with abnormal uterine bleeding: Data mining classification methods. Caspian J Intern Med 2023; 14 (3) :526-533
URL: http://caspjim.com/article-1-3525-en.html


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Volume 14, Issue 3 (Summer 2023) Back to browse issues page
Caspian Journal of Internal Medicine
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