Review for Polycystic Ovary Syndrome (PCOS) detection based on different techniques

The ovaries of the female reproductive organ have a fluid-filled sac called an ovarian cyst. A follicular cyst is a small cyst that usually forms during a woman's menstrual cycle and vanishes at the beginning of the next cycle. Some cysts persist longer than others, causing symptoms like irregular bleeding, heavier or lighter-than-normal flow, and even abdominal pain. These cysts can occasionally appear larger, which will allow them to become polycyst. Because of an imbalance in hormones, polycystic ovarian syndrome (PCOS), results from this. One of the reasons why there are so many fertility clinics in all the nearby cities is due to polycystic ovarian syndrome (PCOS). For the diagnosis of PCOS, ultrasound or ultrasonography (USG) is an effective technique which has been used so far by radiologists and physicians to identify the size of the cyst. In this regard, an Organized Review Process has been made manually by searching different digital libraries related to PCOS study by using the key words. Following this search, 64 papers were selected and put through a review process according to how well they addressed the fields of deep learning, machine learning, and transfer learning in relation to PCOS detection and classification. By critically evaluating recent PCOS studies, 23 papers were reviewed and examined between the year 2020 to 2024, it is possible to identify knowledge gaps and establish direction for future research.