Search results for "NEURAL NETWORK"
showing 10 items of 1385 documents
Factors associated with non-participation and dropout among cancer patients in a cluster-randomised controlled trial
2017
We investigated the impact of demographic and disease related factors on non-participation and dropout in a cluster-randomised behavioural trial in cancer patients with measurements taken between hospitalisation and 6 months thereafter. The percentages of non-participation and dropout were documented at each time point. Factors considered to be potentially related with non-participation and dropout were as follows: age, sex, marital status, education, income, employment status, tumour site and stage of disease. Of 1,338 eligible patients, 24% declined participation at baseline. Non-participation was higher in older patients (Odds Ratio [OR] 2.1, CI: 0.6-0.9) and those with advanced disease …
A deep learning framework for automatic diagnosis of unipolar depression.
2019
Abstract Background and purpose In recent years, the development of machine learning (ML) frameworks for automatic diagnosis of unipolar depression has escalated to a next level of deep learning frameworks. However, this idea needs further validation. Therefore, this paper has proposed an electroencephalographic (EEG)-based deep learning framework that automatically discriminated depressed and healthy controls and provided the diagnosis. Basic procedures In this paper, two different deep learning architectures were proposed that utilized one dimensional convolutional neural network (1DCNN) and 1DCNN with long short-term memory (LSTM) architecture. The proposed deep learning architectures au…
Dropout from Court-Mandated Intervention Programs for Intimate Partner Violence Offenders: The Relevance of Alcohol Misuse and Cognitive Impairments
2019
There is considerable interest in offering insight into the mechanisms that might explain why certain perpetrators of intimate partner violence against women (IPVAW) drop out of interventions. Although several socio-demographic variables and attitudes towards IPVAW have been proposed as risk factors for IPVAW perpetrators&rsquo
Prediction of the hemoglobin level in hemodialysis patients using machine learning techniques
2013
HighlightsDifferent prediction algorithms were used to predict Hb levels in CRF patients.Prediction errors in the validation cohorts of patients were around 0.6g/dl.Difficulty to obtain lower errors due to the measuring machine precision (0.2g/dl).Relevance analysis of features have been applied for each predictor. Patients who suffer from chronic renal failure (CRF) tend to suffer from an associated anemia as well. Therefore, it is essential to know the hemoglobin (Hb) levels in these patients. The aim of this paper is to predict the hemoglobin (Hb) value using a database of European hemodialysis patients provided by Fresenius Medical Care (FMC) for improving the treatment of this kind of …
Disentangling common and specific neural subprocesses of response inhibition.
2012
article i nfo Response inhibition is disturbed in several disorders sharing impulse control deficits as a core symptom. Since response inhibition is a cognitively and neurally multifaceted function which has been shown to rely on differing neural subprocesses and neurotransmitter systems, further differentiation to define neurophys- iological endophenotypes is essential. Response inhibition may involve at least three separable cognitive sub- components, i.e. interference inhibition, action withholding, and action cancelation. Here, we introduce a novel paradigm - the Hybrid Response Inhibition task - to disentangle interference inhibition, action withholding and action cancelation and their…
The what and how of observational learning
2007
Abstract Neuroimaging evidence increasingly supports the hypothesis that the same neural structures subserve the execution, imagination, and observation of actions. We used repetitive transcranial magnetic stimulation (rTMS) to investigate the specific roles of cerebellum and dorsolateral prefrontal cortex (DLPFC) in observational learning of a visuomotor task. Subjects observed an actor detecting a hidden sequence in a matrix and then performed the task detecting either the previously observed sequence or a new one. rTMS applied over the cerebellum before the observational training interfered with performance of the new sequence, whereas rTMS applied over the DLPFC interfered with performa…
pBrain: A novel pipeline for Parkinson related brain structure segmentation
2020
[EN] Parkinson is a very prevalent neurodegenerative disease impacting the life of millions of people worldwide. Although its cause remains unknown, its functional and structural analysis is fundamental to advance in the search of a cure or symptomatic treatment. The automatic segmentation of deep brain structures related to Parkinson's disease could be beneficial for the follow up and treatment planning. Unfortunately, there is not broadly available segmentation software to automatically measure Parkinson related structures. In this paper, we present a novel pipeline to segment three deep brain structures related to Parkinson's disease (substantia nigra, subthalamic nucleus and red nucleus…
Neural net classification of REM sleep based on spectral measures as compared to nonlinear measures
2001
In various studies the implementation of nonlinear and nonconventional measures has significantly improved EEG (electroencephalogram) analyses as compared to using conventional parameters alone. A neural network algorithm well approved in our laboratory for the automatic recognition of rapid eye movement (REM) sleep was investigated in this regard. Originally based on a broad range of spectral power inputs, we additionally supplied the nonlinear measures of the largest Lyapunov exponent and correlation dimension as well as the nonconventional stochastic measures of spectral entropy and entropy of amplitudes. No improvement in the detection of REM sleep could be achieved by the inclusion of …
Neural correlates of interference inhibition, action withholding and action cancelation in adult ADHD
2011
Attention-Deficit/Hyperactivity Disorder (ADHD) is marked by inhibitory and attentional deficits which can persist into adulthood. Those deficits have been associated with dysfunctional fronto-striatal and fronto-parietal circuits. The present study sought to delineate neural correlates of component specific inhibitory deficits in adult ADHD using functional magnetic resonance imaging (fMRI). 20 adult ADHD patients and 24 matched healthy controls were included. Brain activation was assessed during three stages of behavioral inhibition, i.e. interference inhibition (Simon task), action withholding (Go/no-go task) and action cancelation (Stop-signal task). Behaviorally, ADHD patients were aff…
Individuality of movements in music--finger and body movements during playing of the flute.
2013
The achievement of mastery in playing a composition by means of a musical instrument typically requires numerous repetitions and corrections according to the keys and notations of the music piece. Nevertheless, differences in the interpretation of the same music piece by highly skilled musicians seem to be recognizable. The present study investigated differences within and between skilled flute players in their finger and body movements playing the same piece several times on the same and on different days. Six semiprofessional and four professional musicians played an excerpt of Mozart’s Flute Concerto No. 2 several times on three different days. Finger and body movements were recorded by …