Construction of deep learning-based convolutional neural network model for automatic detection of fluid Hysteroscopic endometrial micropolyps in infertile women with chronic endometritis

Deep learning is one of the artificial intelligence models that are actively introduced into clinical practice to assist healthcare providers due to its well-fitting to medical image analysis [1]. One of the most advanced algorithms among the deep learning models is convolutional neural network (CNN). A CNN model comprises a circuit of artificial neurons/nodes that exceed in object recognition and has been developed to the performance of the expert level [2]. The value of the CNN models is that their outputs can provide the probability of the disease, contrary to physicians being able to give only two judgments (presence or absence) [3].

Source: European Journal of Obstetrics, Gynecology, and Reproductive Biology - April 21, 2024 Category: OBGYN Authors: Kotaro Kitaya, Tadahiro Yasuo, Takeshi Yamaguchi, Yuko Morita, Atsumi Hamazaki, Shinji Murayama, Takako Mihara, Masaya Mihara Tags: Full length article Source Type: research