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Automated diagnosis of temporal lobe epilepsy in the absence of interictal spikes.

NeuroImage. Clinical
OBJECTIVE: To diagnose and lateralise temporal lobe epilepsy (TLE) by building a classification system that uses directed functional connectivity patterns estimated during EEG periods without visible pathological activity.

Hand Passive Mobilization Performed with Robotic Assistance: Acute Effects on Upper Limb Perfusion and Spasticity in Stroke Survivors.

BioMed research international
This single arm pre-post study aimed at evaluating the acute effects induced by a single session of robot-assisted passive hand mobilization on local perfusion and upper limb (UL) function in poststroke hemiparetic participants. Twenty-three patients...

Deep convolutional neural network for the automated detection and diagnosis of seizure using EEG signals.

Computers in biology and medicine
An encephalogram (EEG) is a commonly used ancillary test to aide in the diagnosis of epilepsy. The EEG signal contains information about the electrical activity of the brain. Traditionally, neurologists employ direct visual inspection to identify epi...

Delineation of the ischemic stroke lesion based on watershed and relative fuzzy connectedness in brain MRI.

Medical & biological engineering & computing
Precise segmentation of stroke lesions from brain magnetic resonance (MR) images poses a challenging task in automated diagnosis. In this paper, we proposed a new method called watershed-based lesion segmentation algorithm (WLSA), which is a novel in...

Artificial neural network coding of the child attachment interview using linguistic data.

Attachment & human development
Assessing attachment in adolescents is important due to relations between insecurity and psychopathology. The child attachment interview (CAI) holds promise in this regard, but is time-consuming to code, which may render it inaccessible. The aim of t...

Diagnostic accuracy of an artificial neural network compared with statistical quantitation of myocardial perfusion images: a Japanese multicenter study.

European journal of nuclear medicine and molecular imaging
PURPOSE: Artificial neural networks (ANN) might help to diagnose coronary artery disease. This study aimed to determine whether the diagnostic accuracy of an ANN-based diagnostic system and conventional quantitation are comparable.

Construction of environmental risk score beyond standard linear models using machine learning methods: application to metal mixtures, oxidative stress and cardiovascular disease in NHANES.

Environmental health : a global access science source
BACKGROUND: There is growing concern of health effects of exposure to pollutant mixtures. We initially proposed an Environmental Risk Score (ERS) as a summary measure to examine the risk of exposure to multi-pollutants in epidemiologic research consi...

Localization of Origins of Premature Ventricular Contraction by Means of Convolutional Neural Network From 12-Lead ECG.

IEEE transactions on bio-medical engineering
OBJECTIVE: This paper proposes a novel method to localize origins of premature ventricular contractions (PVCs) from 12-lead electrocardiography (ECG) using convolutional neural network (CNN) and a realistic computer heart model.