Search results for "NETWORKS"
showing 10 items of 3260 documents
Motivational factors modulate left frontoparietal network during cognitive control in cocaine addiction
2020
Cocaine addiction is characterized by alterations in motivational and cognitive processes involved in goal-directed behavior. Recent studies have shown that addictive behaviors can be attributed to alterations in the activity of large functional networks. The aim of this study was to investigate how cocaine addiction affected the left frontoparietal network during goal-directed behavior in a stop-signal task (SST) with reward contingencies by correct task performance. Twenty-eight healthy controls (HC) and 30 abstinent cocaine-dependent patients (ACD) performed SST with monetary reward contingencies while undergoing a functional magnetic resonance imaging scan. The results showed that the l…
Evaluation of the Possible Impact of a Care Network for Stroke and Transient Ischemic Attack on Rates of Recurrence
2010
We aimed to demonstrate that a stroke network is able to reduce the proportion of recurrent cerebrovascular events. In 2003, we set up a care network with the aim to reduce the proportion of stroke recurrence. For the statistical analysis, recurrent cerebrovascular events observed from 1985 to 2002 within the population of Dijon made it possible to model trends using Poisson logistic regression. From 1985 to 2002, we recorded 172 recurrent cerebrovascular events which were used to model trends before the creation of the care network. Within the period 2003–2007, we observed 162 recurrent cerebrovascular events compared with 196.7 expected cerebrovascular events with a significant standardiz…
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…
Robust consensus in social networks and coalitional games
2014
We study an n-player averaging process with dynamics subject to controls and adversarial disturbances. The model arises in two distinct application domains: i) coalitional games with transferable utilities (TU) and ii) opinion propagation. We study conditions under which the average allocations achieve robust consensus to some predefined target set.