Computer methods and programs in biomedicine
Jan 12, 2018
The cervical spine is a highly flexible anatomy and therefore vulnerable to injuries. Unfortunately, a large number of injuries in lateral cervical X-ray images remain undiagnosed due to human errors. Computer-aided injury detection has the potential...
Journal of orthopaedic surgery and research
Dec 28, 2017
BACKGROUND: Although measures to reduce and treat the postoperative surgical drain output are discussed, along with the increased interest in causative factors related to the prevention and treatment reported by many studies, these are still controve...
OBJECTIVE: Surgery is one of the riskiest and most important medical acts that is performed today. Understanding the ways in which surgeries are similar or different from each other is of major interest to understand and analyze surgical behaviors. T...
OBJECTIVE: More than half a million surgeries are performed every day worldwide, which makes surgery one of the most important component of global health care. In this context, the objective of this paper is to introduce a new method for the predicti...
Rodent models of spinal cord injury are critical for the development of treatments for upper limb motor impairment in humans, but there are few methods for measuring forelimb strength of rodents, an important outcome measure. We developed a novel rob...
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jun 23, 2015
This study introduces the use of multivariate linear regression (MLR) and support vector regression (SVR) models to predict postoperative outcomes in a cohort of patients who underwent surgery for cervical spondylotic myelopathy (CSM). Currently, pre...
Zhonghua wai ke za zhi [Chinese journal of surgery]
May 1, 2025
Artificial intelligence(AI) is increasingly being utilized in the research of cervical spine diseases, encompassing areas such as image analysis, assisted diagnosis, clinical treatment decision support, surgical assistance, and postoperative rehabili...
PURPOSE: This study was conducted to develop a convolutional neural network (CNN) algorithm that can diagnose cervical foraminal stenosis using oblique radiographs and evaluate its accuracy.
OBJECTIVE: To demonstrate that a T2 periodically rotated overlapping parallel lines with enhanced reconstruction (PROPELLER) technique using deep learning reconstruction (DLR) will provide better image quality and decrease image noise.