Publication: Current Status and Future Potential of Machine Learning in Diagnostic Imaging of Endometriosis : A Literature Review
Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
Nepal Medical Association
Abstract
Abstract
The presence of endometrial tissue outside the uterus is a defining characteristic of endometriosis, a chronic systemic illness that affects women of childbearing age. Despite its enigmatic nature, laparoscopy remains the gold standard for diagnosis, while noninvasive methods such as transvaginal ultrasonography and magnetic resonance imaging are commonly used to aid in preoperative planning. In healthcare, AI has emerged as a game-changing innovation, enhancing patient outcomes, reducing costs, and revolutionizing healthcare delivery, particularly in diagnostic radiology. Images can be analyzed using machine learning, a pattern recognition method. The machine learning algorithm first computes the image characteristics deemed significant for making predictions or diagnoses about unseen images.
Description
Palpasa Shrestha
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, People's Republic of China
Bibek Shrestha
Department of Radiology, Zhongnan Hospital of Wuhan University, Hubei Province, People's Republic of China
Jati Shrestha
National Trauma Center, Mahankal, Kathmandu, Nepal.
Jun Chen
Department of Radiology, Renmin Hospital of Wuhan University, Wuhan, Hubei Province, People's Republic of China