Henrique Mendonca Abrão

OBJECTIVE: To develop a machine learning method for the automatic recognition of endometriosis lesions during laparoscopic surgery and evaluate its feasibility and performance. DESIGN: Collecting and annotating surgical videos and training…

Background: Laparoscopic surgery for endometriosis presents unique challenges due to the complexity of and variability in lesion appearances within the abdominal cavity. This study investigates the application of deep learning models for ob…

OBJECTIVE: to evaluate the association between symptoms and the site of endometriosis lesions using machine learning analysis. DESIGN: retrospective study. SETTING: Two tertiary hospitals. PARTICIPANTS: A total of 726 patients undergoing…

OBJECTIVE: To evaluate the relationship between genetic haplotypes associated with celiac disease (Human Leucocyte Antigen [HLA] DQ2 and DQ8) with the diagnosis, clinical presentation, and location of endometriosis in Brazilian women. METH…

Laparoscopic surgery for endometriosis presents unique challenges due to the complexity and variability of lesion appearances within the abdominal cavity. This study investigates the application of deep learning models for object detection …

Establishing objective criteria to assess endometriosis symptoms is crucial in defining therapeutic strategies. The visual analogue scale (VAS) is the most used system to enhance the accuracy and reduce the subjectivity of pain assessment, …