Endometriosis affects approximately 10% of women of reproductive age and is associated with increased risks of infertility and miscarriage. Although the spontaneous miscarriage rate in women with endometriosis is higher …
This study explores the relationship between inflammatory biomarkers and the risk of endometriosis, aiming to develop a predictive model using National Health and Nutrition Examination Survey (1999-2006) data. The dataset …
Endometriosis is a long-term health problem that affects a significant number of women globally. Among the various forms of endometriosis, ovarian endometriosis (OEM) is the most prevalent. This research aimed …
This study aims to develop a machine learning-based predictive model for patients with endometriosis, with the goal of precisely identifying key factors and reliable predictive markers that influence live birth …
Fresh embryo transfer reduces waiting time and minimizes embryo cryodamage for endometriosis (EM) patients. The current prediction models for fresh embryo transfer outcomes in EM primarily rely on logistic regression, …
Endometriosis significantly impacts the quality of life (QoL) of affected women due to its complex symptomatology. This study aimed to develop a decision tree-based model to identify the key determinants …
Endometriosis is a common chronic neuroinflammatory disease with a poorly understood pathogenesis. Molecular changes and specific immune cell infiltration in the eutopic endometrium are critical to disease progression. This study …
To investigate the factors influencing recurrence following laparoscopic conservative surgery in patients with ovarian endometriosis (OEM) and to develop a predictive model.
Endometriosis (EMs) is the prevalent gynecological disease with the typical features of intricate pathogenesis and immune-related factors. Currently, there is no effective therapeutic intervention for EMs. Disulfidptosis, the cell death …
Could a predictive model, using data from all US fertility clinics reporting to the Society for Assisted Reproductive Technology, estimate the likelihood of patients using their stored oocytes?