Author:
Lv Wenqi,Song Ying,Fu Rongxin,Lin Xue,Su Ya,Jin Xiangyu,Yang Han,Shan Xiaohui,Du Wenli,Huang Qin,Zhong Hao,Jiang Kai,Zhang Zhi,Wang Lina,Huang Guoliang
Abstract
The high prevalence of polycystic ovary syndrome (PCOS) among reproductive-aged women has attracted more and more attention. As a common disorder that is likely to threaten women’s health physically and mentally, the detection of PCOS is a growing public health concern worldwide. In this paper, we proposed an automated deep learning algorithm for the auxiliary detection of PCOS, which explores the potential of scleral changes in PCOS detection. The algorithm was applied to the dataset that contains the full-eye images of 721 Chinese women, among which 388 are PCOS patients. Inputs of the proposed algorithm are scleral images segmented from full-eye images using an improved U-Net, and then a Resnet model was applied to extract deep features from scleral images. Finally, a multi-instance model was developed to achieve classification. Various performance indices such as AUC, classification accuracy, precision, recall, precision, and F1-score were adopted to assess the performance of our algorithm. Results show that our method achieves an average AUC of 0.979 and a classification accuracy of 0.929, which indicates the great potential of deep learning in the detection of PCOS.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Subject
Endocrinology, Diabetes and Metabolism
Cited by
12 articles.
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1. Attention-Based Multiscale Deep Neural Network for Diagnosis of Polycystic Ovary Syndrome Using Ovarian Ultrasound Images;2023 15th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT);2023-10-30
2. An Experimental Analysis Based on Automated Detection of Polycystic Ovary Syndrome on Ultrasound Image using Deep Learning Models;2023 First International Conference on Advances in Electrical, Electronics and Computational Intelligence (ICAEECI);2023-10-19
3. Machine Learning Solutions to Polycystic Ovary Syndrome: A Review;2023 6th International Conference on Contemporary Computing and Informatics (IC3I);2023-09-14
4. IPAD: Iterative pruning with activation deviation for sclera biometrics;Journal of King Saud University - Computer and Information Sciences;2023-09
5. Transfer-Based Deep Learning Technique for PCOS Detection Using Ultrasound Images;2023 International Conference on Network, Multimedia and Information Technology (NMITCON);2023-09-01