Pelvic adhesions are a common consequence of prior abdominal surgery, endometriosis, malignancy, or infection, often leading to infertility, chronic pelvic pain, and surgical complications. Reliable preoperative prediction of these adhesions …
Endometriosis is a chronic inflammatory disease characterized by ectopic endometrial tissue growth, causing pain and infertility. Diagnosis is often delayed due to reliance on imaging and invasive methods, highlighting the …
Endometriosis is a prevalent gynecological condition affecting approximately 10% of women of reproductive age and up to 50% of those with infertility. It is characterized by the presence of endometrial-like …
The Deep Pelvic Endometriosis Index (dPEI) is a preoperative MRI-based score initially validated to predict surgical outcomes in patients undergoing laparoscopic treatment for deep pelvic endometriosis (DPE). Its applicability in …
This study is the first to develop and evaluate a machine learning (ML) model for predicting pelvic adhesions based on ultrasound features, utilizing the SHapley Additive Explanations (SHAP) framework for …
Uterine fibroids and endometriosis are common benign gynecological diseases affecting the health of women of childbearing age, characterized by high incidence and recurrence rates. Despite the increasing global emphasis on …
This study aimed to construct and validate a nomogram for predicting natural pregnancy after hysteroscopy and laparoscopy in patients with tubal infertility and pelvic endometriosis, providing a basis for precise …
Follicle-stimulating hormone receptor (FSHR) is expressed on the plasma membrane of granulosa cells in the ovarian follicles. FSHR is involved in the development and maturation of Graafian follicles, along with …
What was done? A review of artificial intelligence (AI) applications for the imaging of uterine fibroids, endometriosis, and adenomyosis. What was found? AI models can assist with the recognition, segmentation, …