Using the Theory of Planned Behavior to predict information- and support-seeking on Facebook in people with endometriosis.
Many people with endometriosis want to learn more about their condition and connect with others for support. Frequently they turn to social media site Facebook to do so. This study …
Serum-derived small extracellular vesicles as biomarkers for predicting pregnancy and delivery on assisted reproductive technology in patients with endometriosis - Frontiers
Serum-derived small extracellular vesicles as biomarkers for predicting pregnancy and delivery on assisted reproductive technology in patients with endometriosis Frontiers
Anogenital distance on MRI does not correlate to surgical diagnosis of endometriosis in patients without prior abdominal surgery.
Anogenital distance (AGD) is regarded as a potential biomarker for endometriosis, and a measurement on MRI images has been found to be promising. This study aimed to evaluate the measurement …
Influencing factors and prediction model construction for recurrence in patients with ovarian endometriosis after laparoscopic conservative surgery.
To investigate the factors influencing recurrence following laparoscopic conservative surgery in patients with ovarian endometriosis (OEM) and to develop a predictive model.
A Nomogram Model for Predicting Clinical Pregnancy after Fresh IVF/ICSI-ET in Patients with Infertility and Endometriosis.
To determine the clinical and embryo laboratory factors that affect the clinical pregnancy rate of infertile patients with endometriosis (EMs), and establish a model for predicting clinical pregnancy.
Evaluating systemic immune-inflammation indices as predictive markers for endometriosis diagnosis: A retrospective observational study.
Endometriosis is a chronic inflammatory disease for which there is currently no accurate screening test to identify or predict the probability of the disease in individuals. This can often lead …
Assessing the Accuracy of Cardiovascular Disease Prediction Using Female-Specific Risk Factors in Women Aged 45 to 69 Years in the UK Biobank Study.
Cardiovascular disease (CVD) is the leading cause of mortality in women. We aimed to assess whether adding female-specific risk factors to traditional factors could improve CVD risk prediction.