Search results for "Neural Networks"
showing 10 items of 599 documents
An ensemble analysis of electromyographic activity during whole body pointing with the use of support vector machines.
2011
Import JabRef | WosArea Life Sciences and Biomedicine - Other Topics; International audience; We explored the use of support vector machines (SVM) in order to analyze the ensemble activities of 24 postural and focal muscles recorded during a whole body pointing task. Because of the large number of variables involved in motor control studies, such multivariate methods have much to offer over the standard univariate techniques that are currently employed in the field to detect modifications. The SVM was used to uncover the principle differences underlying several variations of the task. Five variants of the task were used. An unconstrained reaching, two constrained at the focal level and two …
Online detection of rem sleep based on the comprehensive evaluation of short adjacent eeg segments by artificial neural networks
1997
Abstract 1. 1. For scientific and clinical requirements the present objective is a robust automatic online algorithm to detect rapid eye movement (REM) steep from single channel sleep EEG data without using EMG or EOG information. 2. 2. For data preprocessing 20 seconds time periods of the continuous EEG activity are digitally filtered in 7 frequency bands. Then the RMS values of these filtered signals are calculated along segments of 2.5 seconds. The resulting matrix of RMS values is representing information on the power of the signal localized in time and frequency and serves as input to an artificial neural network. A pooled set of EEG data together with the corresponding manual evaluati…
Automatic Evaluation of Histological Prognostic Factors Using Two Consecutive Convolutional Neural Networks on Kidney Samples
2022
BACKGROUND AND OBJECTIVES: The prognosis of patients undergoing kidney tumor resection or kidney donation is linked to many histologic criteria. These criteria notably include glomerular density, glomerular volume, vascular luminal stenosis, and severity of interstitial fibrosis/tubular atrophy. Automated measurements through a deep-learning approach could save time and provide more precise data. This work aimed to develop a free tool to automatically obtain kidney histologic prognostic features. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: In total, 241 samples of healthy kidney tissue were split into three independent cohorts. The “Training” cohort (n=65) was used to train two convoluti…
Automatic detection and quantification of ground-glass opacities on high-resolution CT using multiple neural networks: comparison with a density mask.
2000
We compared multiple neural networks with a density mask for the automatic detection and quantification of ground-glass opacities on high-resolution CT under clinical conditions.Eighty-four patients (54 men and 30 women; age range, 18-82 years; mean age, 49 years) with a total of 99 consecutive high-resolution CT scans were enrolled in the study. The neural network was designed to detect ground-glass opacities with high sensitivity and to omit air-tissue interfaces to increase specificity. The results of the neural network were compared with those of a density mask (thresholds, -750/-300 H), with a radiologist serving as the gold standard.The neural network classified 6% of the total lung a…
Influence of somatosensory input on motor function in patients with chronic stroke.
2004
In healthy volunteers, reduction of somatosensory input from one hand leads to rapid performance improvements in the other hand. Thus, it is possible that reduction of somatosensory input from the healthy hand can influence motor function in the paretic hand of chronic stroke patients with unilateral hand weakness. To test this hypothesis, we had 13 chronic stroke patients perform motor tasks with the paretic hand and arm during cutaneous anesthesia of the healthy hand and healthy foot in separate sessions. Performance of a finger tapping task, but not a wrist flexion task, improved significantly with anesthesia of the hand, but not the foot. This effect progressed with the duration of anes…
Peri-Tumoral Inflammatory Cell Infiltration in OSCC: A Reliable Marker of Local Recurrence and Prognosis? An Investigation Using Artificial Neural Ne…
2011
The presence of inflammatory reaction in peri-tumoural connective tissue is generally considered as a defense mechanism against cancer, but inflammation tissue in malignant transformation and early steps of oncogenesis has been recently proven to play a supporting and aggravating role in some carcinomas. Aims of this retrospective study were to evaluate in OSCCs the independent association of peri-tumoral inflammatory infiltrate (PTI) with local recurrence (LR) or survival outcome, and to verify whether PTI can be considered a marker of prognosis. Data from 211 cases of OSCC, only surgically treated between 1990 and 2000, were collected and retrospectively analyzed for PTI and the event LR…
Appropriateness guidelines and predictive rules to select patients for upper endoscopy: a nationwide multicenter study.
2010
OBJECTIVES: Selecting patients appropriately for upper endoscopy (EGD) is crucial for efficient use of endoscopy. The objective of this study was to compare different clinical strategies and statistical methods to select patients for EGD, namely appropriateness guidelines, age and/or alarm features, and multivariate and artificial neural network (ANN) models. METHODS: A nationwide, multicenter, prospective study was undertaken in which consecutive patients referred for EGD during a 1-month period were enrolled. Before EGD, the endoscopist assessed referral appropriateness according to the American Society for Gastrointestinal Endoscopy (ASGE) guidelines, also collecting clinical and demogra…
Artificial Neural Network for Predicting Iodine Deficiency in the First Trimester of Pregnancy in Healthy Women
2020
Iodine deficiency in Spain is a persisting public health problem and the prescription of potassium iodide is recommended during pregnancy. The purpose of this study was to develop an Artificial Neural Network (ANN) to predict the risk factors of iodine deficiency during pregnancy, and compare the results obtained with a logistic regression model. Two hundred forty-four healthy pregnant women were included in a descriptive and prospective study in their first trimester of pregnancy. The women enrolled were asked specifically about their use of supplements containing potassium iodide, iron, folic acid and/or multivitamins during pregnancy. The consumption of iodine-rich foods was assessed thr…
Neural Network for Estimating Energy Expenditure in Paraplegics from Heart Rate
2014
The aim of the present study is to obtain models for estimating energy expenditure based on the heart rates of people with spinal cord injury without requiring individual calibration. A cohort of 20 persons with spinal cord injury performed a routine of 10 activities while their breath-by-breath oxygen consumption and heart rates were monitored. The minute-by-minute oxygen consumption collected from minute 4 to minute 7 was used as the dependent variable. A total of 7 features extracted from the heart rate signals were used as independent variables. 2 mathematical models were used to estimate the oxygen consumption using the heart rate: a multiple linear model and artificial neural networks…
Polar bosons in one-dimensional disordered optical lattices
2013
We analyze the effects of disorder and quasi-disorder on the ground-state properties of ultra-cold polar bosons in optical lattices. We show that the interplay between disorder and inter-site interactions leads to rich phase diagrams. A uniform disorder leads to a Haldane-insulator phase with finite parity order, whereas the density-wave phase becomes a Bose-glass at very weak disorder. For quasi-disorder, the Haldane insulator connects with a gapped generalized incommesurate density wave without an intermediate critical region.