Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Low level of physical activity in women with rheumatoid arthritis is associated with cardiovascular risk factors but not with body fat mass - a cross sectional study

<p>Abstract</p> <p>Background</p> <p>As many patients with rheumatoid arthritis (RA) have increased fat mass (FM) and increased frequency of cardiovascular diseases we evaluated if total physical activity (MET-hours) had impact on body composition and cardiovascular risk factors in women with RA.</p> <p>Methods</p> <p>Sixty-one out-ward RA women, 60.8 (57.3-64.4) years, answered a self-administered questionnaire, to estimate total daily physical activity during the previous year. Physical activity level was given as metabolic equivalents (MET) × h/day. Diet content was assessed by a food frequency questionnaire and body composition by whole-body dual-energy X-ray absorptiometry. Blood lipids and antibodies against phosphorylcholine (anti-PC) were determined.</p> <p>Results</p> <p>Forty-one percent of the women had BMI > 25, 6% were centrally obese and 80% had FM% > 30%. The median (IQR) total physical activity was 40.0 (37.4-47.7), i.e. the same activity level as healthy Swedish women in the same age. Total physical activity did not significantly correlate with disease activity, BMI or FM%. Disease activity, BMI and FM% did not differ between those in the lowest quartile of total physical activity and those in the highest quartile. However, the women in the lowest quartile of physical activity had lower HDL (p = 0.05), Apo A1 (p = 0.005) and atheroprotective natural anti-PC (p = 0.016) and higher levels of insulin (p = 0.05) and higher frequency of insulin resistance than those in the highest quartile. Women in the lowest quartile consumed larger quantities of saturated fatty acids than those in the highest quartile (p = 0.042), which was associated with high oxidized low-density lipoprotein (oxLDL).</p> <p>Conclusion</p> <p>This cross sectional study demonstrated that RA women with fairly low disease activity, good functional capacity, high FM and high frequency of central obesity had the same total physical activity level as healthy Swedish women in the same age. The amount of total physical activity was not associated with functional capacity or body composition. However, low total physical activity was associated with dyslipidemia, insulin resistance, low levels of atheroprotective anti-PC and consumption of saturated fatty acids, which is of interest in the context of increased frequency of cardiovascular disease in RA.</p

A survey of cost-sensitive decision tree induction algorithms

The past decade has seen a significant interest on the problem of inducing decision trees that take account of costs of misclassification and costs of acquiring the features used for decision making. This survey identifies over 50 algorithms including approaches that are direct adaptations of accuracy based methods, use genetic algorithms, use anytime methods and utilize boosting and bagging. The survey brings together these different studies and novel approaches to cost-sensitive decision tree learning, provides a useful taxonomy, a historical timeline of how the field has developed and should provide a useful reference point for future research in this field

Deployment of spatial attention towards locations in memory representations: an EEG study

Recalling information from visual short-term memory (VSTM) involves the same neural mechanisms as attending to an actually perceived scene. In particular, retrieval from VSTM has been associated with orienting of visual attention towards a location within a spatially-organized memory representation. However, an open question concerns whether spatial attention is also recruited during VSTM retrieval even when performing the task does not require access to spatial coordinates of items in the memorized scene. The present study combined a visual search task with a modified, delayed central probe protocol, together with EEG analysis, to answer this question. We found a temporal contralateral negativity (TCN) elicited by a centrally presented go-signal which was spatially uninformative and featurally unrelated to the search target and informed participants only about a response key that they had to press to indicate a prepared target-present vs. -absent decision. This lateralization during VSTM retrieval (TCN) provides strong evidence of a shift of attention towards the target location in the memory representation, which occurred despite the fact that the present task required no spatial (or featural) information from the search to be encoded, maintained, and retrieved to produce the correct response and that the go-signal did not itself specify any information relating to the location and defining feature of the target

Inducing safer oblique trees without costs

Decision tree induction has been widely studied and applied. In safety applications, such as determining whether a chemical process is safe or whether a person has a medical condition, the cost of misclassification in one of the classes is significantly higher than in the other class. Several authors have tackled this problem by developing cost-sensitive decision tree learning algorithms or have suggested ways of changing the distribution of training examples to bias the decision tree learning process so as to take account of costs. A prerequisite for applying such algorithms is the availability of costs of misclassification. Although this may be possible for some applications, obtaining reasonable estimates of costs of misclassification is not easy in the area of safety. This paper presents a new algorithm for applications where the cost of misclassifications cannot be quantified, although the cost of misclassification in one class is known to be significantly higher than in another class. The algorithm utilizes linear discriminant analysis to identify oblique relationships between continuous attributes and then carries out an appropriate modification to ensure that the resulting tree errs on the side of safety. The algorithm is evaluated with respect to one of the best known cost-sensitive algorithms (ICET), a well-known oblique decision tree algorithm (OC1) and an algorithm that utilizes robust linear programming

The Transporter Classification Database: recent advances

The Transporter Classification Database (TCDB), freely accessible at http://www.tcdb.org, is a relational database containing sequence, structural, functional and evolutionary information about transport systems from a variety of living organisms, based on the International Union of Biochemistry and Molecular Biology-approved transporter classification (TC) system. It is a curated repository for factual information compiled largely from published references. It uses a functional/phylogenetic system of classification, and currently encompasses about 5000 representative transporters and putative transporters in more than 500 families. We here describe novel software designed to support and extend the usefulness of TCDB. Our recent efforts render it more user friendly, incorporate machine learning to input novel data in a semiautomatic fashion, and allow analyses that are more accurate and less time consuming. The availability of these tools has resulted in recognition of distant phylogenetic relationships and tremendous expansion of the information available to TCDB users

A prospective longitudinal in vivo (1)H MR spectroscopy study of the SIV/macaque model of neuroAIDS

BACKGROUND: The neurological complications of HIV infection remain poorly understood. Clinically, in vivo (1)H magnetic resonance spectroscopy (MRS) demonstrates brain injury caused by HIV infection even when the MRI is normal. Our goal was to undertsand the dynamics of cerebral injury by performing a longitudinal in vivo (1)H MRS study of the SIV/macaque model of neuroAIDS. RESULTS: Eight rhesus macaques were infected with SIVmac251 and serially imaged with MRI and (1)H MRS to terminal AIDS or the endpoint of 2 years. During acute infection, there were stereotypical brain MRS changes, dominated by a significant elevation of the Cho/Cr ratio in the frontal cortex. Subsequently, brain metabolic patterns diverged between animals. There was an elevation of basal ganglia Cho/Cr four weeks post-inoculation in 2 animals that developed SIV encephalitis (p = 0.022). Metabolite ratios averaged across all 8 animals were not significantly different from baseline at any time point after 2 weeks post inoculation. However, linear regression analysis on all 8 animals revealed a positive correlation between a change in frontal lobe Cho/Cr and plasma viral load (P < 0.001, R = 0.80), and a negative correlation between NAA/Cr in the basal ganglia and the plasma viral load (P < 0.02, R = -0.73). No MRI abnormalities were detected at any time. CONCLUSIONS: After infection with SIV, macaque brain metabolism changes in a complex manner that is dependent on brain region, host factors and viral load. An elevation of basal ganglia Cho/Cr 4 weeks after SIV infection may be marker of a propensity to develop SIV encephalitis. Elevations of Cho/Cr, often observed in CNS inflammation, were associated with increased plasma viral load during acute and chronic infection. Evidence of neuronal injury in the basal ganglia was associated with increased plasma viral load in the chronic stage of infection. These observations support the use of drugs capable of controlling the viral replication and trafficking of virus into the CNS, and may help explain the reduction in incidence of HIV-associated dementia in the era of HAART despite the inability of most of those drugs to effectively enter the CNS

Prevention of childhood poisoning in the home: overview of systematic reviews and a systematic review of primary studies

Unintentional poisoning is a significant child public health problem. This systematic overview of reviews, supplemented with a systematic review of recently published primary studies synthesizes evidence on non-legislative interventions to reduce childhood poisonings in the home with particular reference to interventions that could be implemented by Children's Centres in England or community health or social care services in other high income countries. Thirteen systematic reviews, two meta-analyses and 47 primary studies were identified. The interventions most commonly comprised education, provision of cupboard/drawer locks, and poison control centre (PCC) number stickers. Meta-analyses and primary studies provided evidence that interventions improved poison prevention practices. Twenty eight per cent of studies reporting safe medicine storage (OR from meta-analysis 1.57, 95% CI 1.22–2.02), 23% reporting safe storage of other products (OR from meta-analysis 1.63, 95% CI 1.22–2.17) and 46% reporting availability of PCC numbers (OR from meta-analysis 3.67, 95% CI 1.84–7.33) demonstrated significant effects favouring the intervention group. There was a lack of evidence that interventions reduced poisoning rates. Parents should be provided with poison prevention education, cupboard/drawer locks and emergency contact numbers to use in the event of a poisoning. Further research is required to determine whether improving poison prevention practices reduces poisoning rates