Publications by authors named "M Mascarenhas-Saraiva"
Anorectal dysfunctions (ARDs) include fecal incontinence (FI) and functional defecation disorders (FDDs). The pelvic floor muscles play a central role in the physiology of continence and defecation. We aimed to investigate the prevalence of sarcopenia in a female group with anorectal dysfunctions and compare them with a healthy female age-matched group.
View Article and Find Full Text PDFArticle Synopsis
- Capsule endoscopy (CE) is a minimally invasive procedure used to examine the gastrointestinal tract, but it can be time-consuming and has limited diagnostic effectiveness in the upper GI tract.
- Researchers developed an artificial intelligence (AI) model using convolutional neural networks (CNN) to automatically detect various types of pleomorphic lesions from a large dataset of CE images, evaluating its performance against expert classifications.
- The AI model demonstrated high diagnostic accuracy across different areas of the GI tract, with the best results being 96.6% accuracy for gastric lesions and 97.6% for small bowel lesions, suggesting that AI tools could significantly enhance the effectiveness of capsule panendoscopy.
Article Synopsis
- - Capsule endoscopy (CE) is a key tool for assessing inflammation in Crohn's disease, traditionally evaluated using scores like Lewis score, CECDAI, and ELIAKIM, but recent AI advancements allow for automated frame selection in CE videos.
- - In this proof-of-concept study involving 61 patients, researchers developed an AI-based scoring system that correlated well with traditional inflammation scores, showing strong statistical relationships between their automated score and established metrics.
- - The findings suggest that the AI-generated score is a reliable and objective method for evaluating inflammation in Crohn's disease, laying the groundwork for further advancements in CE technology.
Capsule endoscopy (CE) is commonly used as the initial exam for suspected mid-gastrointestinal bleeding after normal upper and lower endoscopy. Although the assessment of the small bowel is the primary focus of CE, detecting upstream or downstream vascular lesions may also be clinically significant. This study aimed to develop and test a convolutional neural network (CNN)-based model for panendoscopic automatic detection of vascular lesions during CE.
View Article and Find Full Text PDFAn estimation of the biomechanical properties of the continent and incontinent woman bladder via inverse finite element analysis.
Proc Inst Mech Eng H
June 2024
Article Synopsis
- Stress urinary incontinence is caused by weakening or damage of pelvic support structures due to factors like aging, vaginal delivery, and obesity, which can change the biomechanical properties of bladder tissue.* -
- The study utilizes inverse finite element analysis and MRI to estimate the bladder's biomechanical properties in two groups of women: continent (G1) and incontinent (G2), revealing that bladder tissue in the incontinent group is about 47% stiffer than in the continent group.* -
- Understanding these biomechanical properties can help in selecting tailored synthetic mesh treatments for pelvic dysfunction, utilizing a non-invasive approach to assess individual conditions.*