INTRODUCTION: Functional electrical stimulation (FES) synchronized with robot-assisted lower extremity training is used in spinal cord injury (SCI) rehabilitation to promote residual function.
Journal of clinical monitoring and computing
Sep 3, 2022
Accurate estimation of surgical risks is important for informing the process of shared decision making and informed consent. Postoperative reintubation (POR) is a severe complication that is associated with postoperative morbidity. Previous studies h...
OBJECTIVE: About 3% of primary pyeloplasties may require a re-do pyeloplasty for recurrent uretero pelvic junction obstruction (UPJO) making it an uncommon operation even in large volume centers. In this MA we have compared the outcomes of open (OP),...
In this article, the upgrading process of the structure-based virtual screening (SBVS) protocol targeting acetylcholinesterase (AChE) previously published in 2017 is presented. The upgraded version of PyPLIF called PyPLIF HIPPOS and the receptor ense...
Radiomics and machine learning-based methods offer exciting opportunities for improving diagnostic performance and efficiency in musculoskeletal radiology for various tasks, including acute injuries, chronic conditions, spinal abnormalities, and neop...
OBJECTIVES: The aim of this study was to develop and validate a deep learning-based algorithm (DLA) for automatic detection and grading of motion-related artifacts on arterial phase liver magnetic resonance imaging (MRI).
AJR. American journal of roentgenology
Aug 31, 2022
CT-based body composition (BC) measurements have historically been too resource intensive to analyze for widespread use and have lacked robust comparison with traditional weight metrics for predicting cardiovascular risk. The aim of this study was ...
Breast Cancer (BC) is the most commonly diagnosed cancer and second leading cause of mortality among women. About 1 in 8 US women (about 13%) will develop invasive BC throughout their lifetime. Early detection of this life-threatening disease not onl...
The aim of the work described here was to develop an ultrasound (US) image-based deep learning model to reduce the rate of malignancy among breast lesions diagnosed as category 4A of the Breast Imaging-Reporting and Data System (BI-RADS) during the p...
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