To develop and internally validate machine-learning models for non-invasive triage of women at risk for endometriosis using structured clinical variables in a laparoscopically and histologically verified cohort.
Endometriosis affects an estimated 5-10% of women of reproductive age and presents with substantial clinical and biological heterogeneity. Recent clinical guidelines have shifted toward symptom-guided diagnosis supported by expert imaging, …
Telemedicine may advance endometriosis care, but few initiatives are integrated in outpatient follow-up. A novel telemedicine approach-tele-patient-reported outcome measures (telePROM)-includes an endometriosis-specific questionnaire and phone and video consultations combined with …
Early diagnosis of ovarian cancer remains one of the most important unmet needs in gynecologic oncology because survival is strongly stage-dependent and most patients still present with disseminated disease. Conventional …
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 …
To develop and validate models to predict which endometriosis patients are likely to experience pain reduction following therapeutic laparoscopy using intraoperative findings and patient characteristics.
Patient-Reported Outcome (PRO) measures supported by a severity algorithm may serve as a decision aid for triage and consultation in follow-up of patients with endometriosis. In a new follow-up regime, …