101 resultados para Illiac computer.


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Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as the starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer's disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with a total of 29 algorithms. The algorithms were trained on a small training set (n = 30) and optionally on data from other sources (e.g., the Alzheimer's Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework: http://caddementia.grand-challenge.org.

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Dietary assessment in older adults can be challenging. The Novel Assessment of Nutrition and Ageing (NANA) method is a touch-screen computer-based food record that enables older adults to record their dietary intakes. The objective of the present study was to assess the relative validity of the NANA method for dietary assessment in older adults. For this purpose, three studies were conducted in which a total of ninety-four older adults (aged 65–89 years) used the NANA method of dietary assessment. On a separate occasion, participants completed a 4 d estimated food diary. Blood and 24 h urine samples were also collected from seventy-six of the volunteers for the analysis of biomarkers of nutrient intake. The results from all the three studies were combined, and nutrient intake data collected using the NANA method were compared against the 4 d estimated food diary and biomarkers of nutrient intake. Bland–Altman analysis showed a reasonable agreement between the dietary assessment methods for energy and macronutrient intake; however, there were small, but significant, differences for energy and protein intake, reflecting the tendency for the NANA method to record marginally lower energy intakes. Significant positive correlations were observed between urinary urea and dietary protein intake using both the NANA and the 4 d estimated food diary methods, and between plasma ascorbic acid and dietary vitamin C intake using the NANA method. The results demonstrate the feasibility of computer-based dietary assessment in older adults, and suggest that the NANA method is comparable to the 4 d estimated food diary, and could be used as an alternative to the food diary for the short-term assessment of an individual’s dietary intake.

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Nine chess programs competed in July 2015 in the ICGA's World Computer Chess Championship at the Computer Science department of Leiden University. This is the official report of the event.

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A Brain-computer music interface (BCMI) is developed to allow for continuous modification of the tempo of dynamically generated music. Six out of seven participants are able to control the BCMI at significant accuracies and their performance is observed to increase over time.

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OBJECTIVE: Assimilating the diagnosis complete spinal cord injury (SCI) takes time and is not easy, as patients know that there is no 'cure' at the present time. Brain-computer interfaces (BCIs) can facilitate daily living. However, inter-subject variability demands measurements with potential user groups and an understanding of how they differ to healthy users BCIs are more commonly tested with. Thus, a three-class motor imagery (MI) screening (left hand, right hand, feet) was performed with a group of 10 able-bodied and 16 complete spinal-cord-injured people (paraplegics, tetraplegics) with the objective of determining what differences were present between the user groups and how they would impact upon the ability of these user groups to interact with a BCI. APPROACH: Electrophysiological differences between patient groups and healthy users are measured in terms of sensorimotor rhythm deflections from baseline during MI, electroencephalogram microstate scalp maps and strengths of inter-channel phase synchronization. Additionally, using a common spatial pattern algorithm and a linear discriminant analysis classifier, the classification accuracy was calculated and compared between groups. MAIN RESULTS: It is seen that both patient groups (tetraplegic and paraplegic) have some significant differences in event-related desynchronization strengths, exhibit significant increases in synchronization and reach significantly lower accuracies (mean (M) = 66.1%) than the group of healthy subjects (M = 85.1%). SIGNIFICANCE: The results demonstrate significant differences in electrophysiological correlates of motor control between healthy individuals and those individuals who stand to benefit most from BCI technology (individuals with SCI). They highlight the difficulty in directly translating results from healthy subjects to participants with SCI and the challenges that, therefore, arise in providing BCIs to such individuals.

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OBJECTIVE: Interferences from spatially adjacent non-target stimuli are known to evoke event-related potentials (ERPs) during non-target flashes and, therefore, lead to false positives. This phenomenon was commonly seen in visual attention-based brain-computer interfaces (BCIs) using conspicuous stimuli and is known to adversely affect the performance of BCI systems. Although users try to focus on the target stimulus, they cannot help but be affected by conspicuous changes of the stimuli (such as flashes or presenting images) which were adjacent to the target stimulus. Furthermore, subjects have reported that conspicuous stimuli made them tired and annoyed. In view of this, the aim of this study was to reduce adjacent interference, annoyance and fatigue using a new stimulus presentation pattern based upon facial expression changes. Our goal was not to design a new pattern which could evoke larger ERPs than the face pattern, but to design a new pattern which could reduce adjacent interference, annoyance and fatigue, and evoke ERPs as good as those observed during the face pattern. APPROACH: Positive facial expressions could be changed to negative facial expressions by minor changes to the original facial image. Although the changes are minor, the contrast is big enough to evoke strong ERPs. In this paper, a facial expression change pattern between positive and negative facial expressions was used to attempt to minimize interference effects. This was compared against two different conditions, a shuffled pattern containing the same shapes and colours as the facial expression change pattern, but without the semantic content associated with a change in expression, and a face versus no face pattern. Comparisons were made in terms of classification accuracy and information transfer rate as well as user supplied subjective measures. MAIN RESULTS: The results showed that interferences from adjacent stimuli, annoyance and the fatigue experienced by the subjects could be reduced significantly (p < 0.05) by using the facial expression change patterns in comparison with the face pattern. The offline results show that the classification accuracy of the facial expression change pattern was significantly better than that of the shuffled pattern (p < 0.05) and the face pattern (p < 0.05). SIGNIFICANCE: The facial expression change pattern presented in this paper reduced interference from adjacent stimuli and decreased the fatigue and annoyance experienced by BCI users significantly (p < 0.05) compared to the face pattern.

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A fully automated and online artifact removal method for the electroencephalogram (EEG) is developed for use in brain-computer interfacing. The method (FORCe) is based upon a novel combination of wavelet decomposition, independent component analysis, and thresholding. FORCe is able to operate on a small channel set during online EEG acquisition and does not require additional signals (e.g. electrooculogram signals). Evaluation of FORCe is performed offline on EEG recorded from 13 BCI particpants with cerebral palsy (CP) and online with three healthy participants. The method outperforms the state-of the-art automated artifact removal methods Lagged auto-mutual information clustering (LAMIC) and Fully automated statistical thresholding (FASTER), and is able to remove a wide range of artifact types including blink, electromyogram (EMG), and electrooculogram (EOG) artifacts.

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This case series compares patient experiences and therapeutic processes between two modalities of cognitive behaviour therapy (CBT) for depression: computerized CBT (cCBT) and therapist-delivered CBT (tCBT). In a mixed-methods repeated-measures case series, six participants were offered cCBT and tCBT in sequence, with the order of delivery randomized across participants. Questionnaires about patient experiences were administered after each session and a semi-structured interview was completed with each participant at the end of each therapy modality. Therapy expectations, patient experiences and session impact ratings in this study generally favoured tCBT. Participants typically experienced cCBT sessions as less meaningful, less positive and less helpful compared to tCBT sessions in terms of developing understanding, facilitating problem-solving and building a therapeutic relationship.

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This article explores the way users of an online gay chat room negotiate the exchange of photographs and the conduct of video conferencing sessions and how this negotiation changes the way participants manage their interactions and claim and impute social identities. Different modes of communication provide users with different resources for the control of information, affecting not just what users are able to reveal, but also what they are able to conceal. Thus, the shift from a purely textual mode for interacting to one involving visual images fundamentally changes the kinds of identities and relationships available to users. At the same time, the strategies users employ to negotiate these shifts of mode can alter the resources available in different modes. The kinds of social actions made possible through different modes, it is argued, are not just a matter of the modes themselves but also of how modes are introduced into the ongoing flow of interaction.