Results 31 to 40 of about 252,678 (316)
The Association Between Pelvic Discomfort and Erectile Dysfunction in Adult Male Bicyclists. [PDF]
, 2020 BackgroundBicycle riding's impact on erectile function remains a topic of great interest given cycling's popularity as a mode of transportation and exercise.AimWe evaluated risk factors for sexual dysfunction in male cyclists with the primary intention ...
Balasubramanian, Adithya +4 more
core +1 more source
Compression shorts reduce prenatal pelvic and low back pain: a prospective quasi-experimental controlled study [PDF]
, 2019 Background Common prenatal ailments negatively impact performance of activities of daily living and it has been proposed that the use of dynamic elastomeric fabric orthoses, more commonly referred to as compression garments, during pregnancy might aid in
Hing, Wayne +3 more
core +1 more source
Pelvic floor MRI segmentation based on semi-supervised deep learning [PDF]
arXiv, 2023 The semantic segmentation of pelvic organs via MRI has important clinical significance. Recently, deep learning-enabled semantic segmentation has facilitated the three-dimensional geometric reconstruction of pelvic floor organs, providing clinicians with accurate and intuitive diagnostic results.
arxiv
Sexual Medicine, 2020 Introduction: Deep dyspareunia is a cardinal symptom of endometriosis, and as many as 40% of people with this condition experience comorbid superficial dyspareunia.
Kate J. Wahl, MSc +10 more
doaj
Automatic pain recognition from Blood Volume Pulse (BVP) signal using machine learning techniques [PDF]
arXiv, 2023 Physiological responses to pain have received increasing attention among researchers for developing an automated pain recognition sensing system. Though less explored, Blood Volume Pulse (BVP) is one of the candidate physiological measures that could help objective pain assessment. In this study, we applied machine learning techniques on BVP signals to
arxiv
Fully Automated Organ Segmentation in Male Pelvic CT Images [PDF]
Balagopal A, Kazemifar S, Nguyen D, Lin M H, Hannan R, Owrangi A
and Jiang S 2018 Fully automated organ segmentation in male pelvic CT images
Phys. Med. Biol. 63 245015, 2018 Accurate segmentation of prostate and surrounding organs at risk is important for prostate cancer radiotherapy treatment planning. We present a fully automated workflow for male pelvic CT image segmentation using deep learning. The architecture consists of a 2D localization network followed by a 3D segmentation network for volumetric segmentation of ...
arxiv +1 more source
Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings [PDF]
, 2019 Early diagnosis of sacroiliitis may lead to preventive treatment which can significantly improve the patient's quality of life in the long run. Oftentimes, a CT scan of the lower back or abdomen is acquired for suspected back pain. However, since the differences between a healthy and an inflamed sacroiliac joint in the early stages are subtle, the ...
arxiv +1 more source
Equine Pain Behavior Classification via Self-Supervised Disentangled Pose Representation [PDF]
arXiv, 2021 Timely detection of horse pain is important for equine welfare. Horses express pain through their facial and body behavior, but may hide signs of pain from unfamiliar human observers. In addition, collecting visual data with detailed annotation of horse behavior and pain state is both cumbersome and not scalable.
arxiv
Diagnositic value of pelvic enthesitis on MRI of the sacroiliac joints in enthesitis related arthritis [PDF]
, 2015 Background: To determine the prevalence and diagnostic value of pelvic enthesitis on MRI of the sacroiliac (SI) joints in enthesitis related arthritis (ERA).
Baraliakos, X. +10 more
core +1 more source
Advanced Materials Technologies, Volume 10, Issue 6, March 18, 2025.The given research presents an innovative insole‐based device employing self‐powered triboelectric nanogenerators (TENG) for flatfoot detection. By integrating TENG tactile sensors within an insole, the device converts mechanical energy from foot movements to electrical signals analyzed via machine learning, achieving an 82% accuracy rate in flatfoot ...
Moldir Issabek +7 more
wiley +1 more source