Identification of Uterine Disorder using Different Deep Learning Models

Uterine disorders significantly impact women’s reproductive health and overall well-being.The risk factors, early detection methods, and advancement in personalized treatment options, highlighting the importance of a multidisciplinary approach to manage these potentially life-threatening conditions. This paper details various research in diagnosing uterine disorders using a deep learning approach and a comparative study of various models in a deep learning approach in finding PCOS disorder from ultrasound images. Performance measures such as Accuracy, Precision, Recall, Confusion matrix, F1 Score, Training & Validation time and Execution time for prediction, are used to compare the results of different deep learning models.