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ECG authentication system design incorporating a convolutional neural network and generalized S-Transformation.

Computers in biology and medicine
Electrocardiogram (ECG) is gaining increased attention as a biometric method in a wide range of applications, such as access control and security/privacy requirements. The majority of reported investigations using the ECG biometric method are usually...

A wearable hip-assist robot reduces the cardiopulmonary metabolic energy expenditure during stair ascent in elderly adults: a pilot cross-sectional study.

BMC geriatrics
BACKGROUND: Stair ascent is one of the most important and challenging activities of daily living to maintain mobility and independence in elderly adults. Recently, various types of wearable walking assist robots have been developed to improve gait fu...

Optical classification of neoplastic colorectal polyps - a computer-assisted approach (the COACH study).

Scandinavian journal of gastroenterology
BACKGROUND AND AIMS: Clinical data suggest that the quality of optical diagnoses of colorectal polyps differs markedly among endoscopists. The aim of this study was to develop a computer program that was able to differentiate neoplastic from non-neop...

Deep Learning Models Unveiled Functional Difference Between Cortical Gyri and Sulci.

IEEE transactions on bio-medical engineering
It is largely unknown whether there is functional role difference between cortical gyral and sulcal regions. Recent advancements in neuroimaging studies demonstrate clear difference of structural connection profiles in gyral and sulcal areas, suggest...

Effects of hyaluronidase on ropivacaine or bupivacaine regional anaesthesia of the canine pelvic limb.

Veterinary anaesthesia and analgesia
OBJECTIVE: To determine the effect of hyaluronidase on time to onset and offset of anaesthesia in ropivacaine or bupivacaine femoral-ischiatic nerve blocks.

Machine learning for real-time prediction of complications in critical care: a retrospective study.

The Lancet. Respiratory medicine
BACKGROUND: The large amount of clinical signals in intensive care units can easily overwhelm health-care personnel and can lead to treatment delays, suboptimal care, or clinical errors. The aim of this study was to apply deep machine learning method...

Feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy.

Radiological physics and technology
This study aimed to investigate the feasibility of anatomical feature points for the estimation of prostate locations in the Bayesian delineation frameworks for prostate cancer radiotherapy. The relationships between the reference centroids of prosta...

The application of artificial intelligence to understand the pathophysiological basis of psychogenic nonepileptic seizures.

Epilepsy & behavior : E&B
Psychogenic nonepileptic seizures (PNES) are episodes of paroxysmal impairment associated with a range of motor, sensory, and mental manifestations, which perfectly mimic epileptic seizures. Several patterns of neural abnormalities have been describe...

Emergence of spontaneous assembly activity in developing neural networks without afferent input.

PLoS computational biology
Spontaneous activity is a fundamental characteristic of the developing nervous system. Intriguingly, it often takes the form of multiple structured assemblies of neurons. Such assemblies can form even in the absence of afferent input, for instance in...

Deep Learning Analysis of Upright-Supine High-Efficiency SPECT Myocardial Perfusion Imaging for Prediction of Obstructive Coronary Artery Disease: A Multicenter Study.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Combined analysis of SPECT myocardial perfusion imaging (MPI) performed with a solid-state camera on patients in 2 positions (semiupright, supine) is routinely used to mitigate attenuation artifacts. We evaluated the prediction of obstructive disease...