ECG arrhythmia classification based on optimum-path forest

An important tool for the heart disease diagnosis is the analysis of electrocardiogram (ECG) signals, since the non-invasive nature and simplicity of the ECG exam. According to the application, ECG data analysis consists of steps such as preprocessing, segmentation, feature extraction and classification aiming to detect cardiac arrhythmias (i.e.; cardiac rhythm abnormalities). Aiming to made a fast and accurate cardiac arrhythmia signal classification process, we apply and analyze a recent and robust supervised graph-based pattern recognition technique, the optimum-path forest (OPF) classifier. To the best of our knowledge, it is the first time that OPF classifier is used to the ECG heartbeat signal classification task. We then compare the performance (in terms of training and testing time, accuracy, specificity, and sensitivity) of the OPF classifier to the ones of other three well-known expert system classifiers, i.e.; support vector machine (SVM), Bayesian and multilayer artificial neural network (MLP), using features extracted from six main approaches considered in literature for ECG arrhythmia analysis. In our experiments, we use the MIT-BIH Arrhythmia Database and the evaluation protocol recommended by The Association for the Advancement of Medical Instrumentation. A discussion on the obtained results shows that OPF classifier presents a robust performance, i.e.; there is no need for parameter setup, as well as a high accuracy at an extremely low computational cost. Moreover, in average, the OPF classifier yielded greater performance than the MLP and SVM classifiers in terms of classification time and accuracy, and to produce quite similar performance to the Bayesian classifier, showing to be a promising technique for ECG signal analysis. © 2012 Elsevier Ltd. All rights reserved.

Improving the accuracy of the optimum-path forest supervised classifier for large datasets

In this work, a new approach for supervised pattern recognition is presented which improves the learning algorithm of the Optimum-Path Forest classifier (OPF), centered on detection and elimination of outliers in the training set. Identification of outliers is based on a penalty computed for each sample in the training set from the corresponding number of imputable false positive and false negative classification of samples. This approach enhances the accuracy of OPF while still gaining in classification time, at the expense of a slight increase in training time. © 2010 Springer-Verlag.

Classification of intact fresh plums according to sweetness using time-domain nuclear magnetic resonance and chemometrics

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Identification of Candida Spp. In Patients with Denture Stomatitis: Relationship with Gender, Age, Time of Denture use and Newton’s Classification

Epidemiological researches are important to understand the distribution and etiology of oral diseases. The actual researches that show the relationship between patient ages, denture status and denture stomatitis are scarce. So, the aim of this study was to identify of Candida spp. in patients with Denture Stomatitis (DS) and to correlate with gender, age, time of denture use and Newton’s classification. 204 complete denture patients (46 males and 158 females) were selected. DS was classified according to Newton’s classification and it was related to gender, age and time of denture use. Samples from the palatal mucosa and the surface of the upper denture of patients with DS were evaluated using PCR test for identification of Candida species. T-test, chisquare and Fisher’s exact tests were used for statistical analysis. DS was evidenced in 54.4% of the sample. According to gender 41.3% of the males and 58.3% females had the disease and the differences were statistically significant (p = 0.032). The type of DS was directly influenced by the time of denture use (p<0.001), but it was not significantly related to the age of the participants (p>0.05). C. albicans, C. tropicalis, C. glabrata, C. krusei and C. dubliniensis were identified by PCR test. DS is more prevalent in women and the prevalence of DS was influenced by the time of denture use (years). C. albicans was identified as the most frequent specie in patients with DS.

Detection and classification of voltage disturbances using a Fuzzy-ARTMAP-wavelet network

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Arithmetic fuchsian groups and space time block codes

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Submucous fibroids classification - STEP-W classification

Objective: To develop a new submucous fibroids classification for evaluating the viability and the degree of difficulty and complexity of a hysteroscopic myomectomy.Methods: We have included more four parameters in addition to penetration the fibroid into the myometrium. The extra-parameters were: size of the fibroid, it topography, it extension of the base in relation the wall was set and the wall it was set. The fibroids were classified according to the Classification of the European Society for Gynaecological Endoscopy (ESGE) and to the new classification (STEP-W) in patients who were submitted to hysteroscopic resection of submucous fibroids. The possibility of total resection of the fibroid, the operating time, the fluid deficit and the frequency of any complications were considered. The Fisher test, the Student t test and the analysis of variance test were used in the statistical analyses. It was considered statistically significant when the p-value was less than 0.05 in the two-tailed test.Results: In group which the hysteroscopic surgery was considered complete there was no significant difference between the three ESGE levels (0, 1 and 2). Using the STEP-W, the difference between the numbers of complete surgeries was significant (p < 0.001) for the two levels (groups I and II). The difference between the operating times was significant for the two classifications. In relation to the fluid deficit, only the STEP-W showed significant differences between the levels (p=0.02).Conclusions: It seems to us that the new classification (STEP-W) gives more clues to the difficulties of a hysteroscopic myornectomy than the standard classification (ESGE).

Traumatic subdural hygromas: Proposed pathogenesis based classification

Background: Traumatic subdural hygroma (TSHy) is an accumulation of cerebrospinal fluid (CSF) in the subdural space after head injury. It appears to be relatively common, but its onset time and natural history are not well defined. Considered a benign epiphenomenon of trauma, the pathogenesis of TSHy is still unclear and many questions remain unanswered. This study adds to the information on TSHy, and proposes a classification based on pathogenesis.Methods: Thirty-four consecutive adult patients with TSHy were analyzed for clinical evolution and serial CT scan, during a period of several months. TSHy diagnosis was based on published CT scan criteria of hypodense subdural collection after trauma, without enhancement and neomembrane, with a minimum distance of 3 mm between the skull and brain. Ventricle size was analyzed by calculating the bicaudate index (BCI). For comparison, the BCI was measured from CT scan at three moments: admission, at time of TSHy diagnosis, and from last CT scan.Results: There were 34 patients, aged between 16 and 85 years (mean 40), half of them were below 40 years. Road traffic crashes were the main cause of head injury. The mean time for hygroma diagnosis was 9 days. Twenty-one patients (61.8%) underwent conservative treatment for TSHy and 13 (38.2%), surgical treatment. TSHy are early lesions and can be detected in the first 24 hours after trauma, usually as small subdural effusion (SSEff). Based on clinical and CT scan findings, we divided the 34 patients into 3 groups, (Ia and Ib) without evident mass effect and (II) with evident mass effect. Group Ia includes patients without ventricle dilation; Ib, patients with associated ventricle dilations.Conclusions: SSEff detected in the first 24 hours posttrauma in our series evolved into TSHy suggesting that this is an early lesion; all THSy were divided in three groups according to the pathophysiologic mechanism. These three groups probably represent a continuum of CSF absorption impairment. Group la represents what most authors consider a simple hygroma, with no impairment on CSF absorption. Group Ib represent the external hydrocephalus form with various degrees of CSF imbalance, and group II were the cases presenting marked mass effect.

C programs for solving the time-dependent Gross-Pitaevskii equation in a fully anisotropic trap

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Submucous myomas: A new presurgical classification to evaluate the viability of hysteroscopic surgical treatment - Preliminary report

STUDY OBJECTIVE: To develop a new preoperative classification of submucous myomas for evaluating the viability and the degree of difficulty of hysteroscopic myomectomy.DESIGN: Retrospective study (Canadian Task Force classification II-3)SETTING: University teaching hospitals.PATIENTS: Fifty-five patients who underwent hysteroscopic resection of submucous myomas.INTERVENTION: the possibility of total resection of the myoma, the operating time, the fluid deficit, and the frequency of any complications were considered. The myomas were classified according to the Classification of the European Society for Gynaecological Endoscopy (ESGE) and by our group's new classification (NC), which considers not only the degree of penetration of the myoma into the myometrium, but also adds in such parameters as the distance of the base of the myoma from the uterine wall, the size of the nodule (cm), and the topography of the uterine cavity. The Fisher's exact test, the Student's t test, and the analysis of variance test were used in the statistical analysis. A p value less than .05 in the two-tailed test was considered significant.MEASUREMENTS AND MAIN RESULTS: In 57 myomas, hysteroscopic surgery was considered complete. There was no significant difference among the three ESGE levels (0, 1, and 2). Using the NC, the difference between the numbers of complete surgeries was significant (p < .001) for the two levels (groups I and H). The difference between the operating times was significant for the two classifications. With respect to the fluid deficit, only the NC showed significant differences between the levels (p = .02).CONCLUSIONS: We believe that the NC gives more clues as to the difficulties of a hysteroscopic myomectomy than the standard ESGE classification. It should be stressed that the number of hysteroscopic myomectomies used in this analysis was low, and it would be interesting to evaluate the performance of the classification in a larger number of patients. (c) 2005 AAGL. All rights reserved.

A Fast Large Scale Iris Database Classification with Optimum-Path Forest Technique: A Case Study

Majority of biometric researchers focus on the accuracy of matching using biometrics databases, including iris databases, while the scalability and speed issues have been neglected. In the applications such as identification in airports and borders, it is critical for the identification system to have low-time response. In this paper, a graph-based framework for pattern recognition, called Optimum-Path Forest (OPF), is utilized as a classifier in a pre-developed iris recognition system. The aim of this paper is to verify the effectiveness of OPF in the field of iris recognition, and its performance for various scale iris databases. This paper investigates several classifiers, which are widely used in iris recognition papers, and the response time along with accuracy. The existing Gauss-Laguerre Wavelet based iris coding scheme, which shows perfect discrimination with rotary Hamming distance classifier, is used for iris coding. The performance of classifiers is compared using small, medium, and large scale databases. Such comparison shows that OPF has faster response for large scale database, thus performing better than more accurate but slower Bayesian classifier.

Brazilian consensus on gastroesophageal reflux disease: Proposals for assessment, classification, and management

The Brazilian Consensus on Gastroesophageal Reflux Disease considers gastroesophageal reflux disease to be a chronic disorder related to the retrograde flow of gastroduodenal contents into the esophagus and/or adjacent organs, resulting in a variable spectrum of symptoms, with or without tissue damage. Considering the limitations of classifications currently in use, a new classification is proposed that combines three criteria - clinical, endoscopic, and pH-metric - providing a comprehensive and more complete characterization of the disease. The diagnosis begins with the presence of heartburn, acid regurgitation, and alarm manifestations (dysphagia, odynophagia, weight loss, GI bleeding, nausea and/or vomiting, and family history of cancer). Also, atypical esophageal, pulmonary, otorhinolaryngological, and oral symptoms may occur. Endoscopy is the first approach, particularly in patients over 40 yr of age and in those with alarm symptoms. Other exams are considered in particular cases, such as contrast radiological examination, scyntigraphy, manometry, and prolonged pH measurement. The clinical treatment encompasses behavioral modifications in lifestyle and pharmacological measures. Proton pump inhibitors in manufacturers' recommended doses are indicated, with doubling of the dose in more severe cases of esophagitis. The minimum time of administration is 6 wk. Patients who do not respond to medical treatment, including those with atypical manifestations, should be considered for surgical treatment. Of the complications of gastroesophageal reflux disease, Barrett's esophagus presents a potential development of adenocarcinoma; biopsies should be performed, independent of Barrett's esophagus extent or location. In this regard the designation short Barrett's is not important in terms of management and prognosis. © 2002 by Am. Coll. of Gastroenterology.

Shape-based features for cat ganglion retinal cells classification

This article presents a quantitative and objective approach to cat ganglion cell characterization and classification. The combination of several biologically relevant features such as diameter, eccentricity, fractal dimension, influence histogram, influence area, convex hull area, and convex hull diameter are derived from geometrical transforms and then processed by three different clustering methods (Ward's hierarchical scheme, K-means and genetic algorithm), whose results are then combined by a voting strategy. These experiments indicate the superiority of some features and also suggest some possible biological implications.

Method for the evaluation of insecticidal activity over time in Atta sexdens rubropilosa workers (Hymenoptera: Formicidae)

The active ingredients used in the formulation of toxic baits for leaf-cutting ants (Hymenoptera: Formicidae) should possess a delayed action defined as an insecticidal activity whereby worker mortality is ≤15% at 24 hours and ≥90% at 21 days. Serious shortcomings have occurred in the search for new active ingredients, such as the initial selection of fenoxycarb, copper oxychloride and diflubenzuron, compounds considered very promising but whose inefficiency was verified only later, indicating methodological problems. In view of this situation, we developed a classification method for insecticidal activity over time using workers of the leaf-cutting ant Atta sexdens rubropilosa Forel. The insecticides used were fipronil, sulfluramid GX071HB and sulfluramid GX439, vehicled in an attractive pasty formulation prepared based on citrus pulp. The results obtained were consistent from a toxicological viewpoint and agreed with the literature in terms of the control of colonies. Sulfluramids were found to possess a delayed action at a broad range of concentrations, in agreement with the fact that these substances are highly effective in the control of all leaf-cutting ant species. The smaller range of concentrations of fipronil with delayed action is probably related to its lower efficacy for species more difficult to control such as Atta capiguara (Forti et al. 2003). We discuss the importance of relating behavioral particularities to the specific feeding habits of leaf-cutting ants, with methodological adequacy of the assessment of insecticides aimed at toxic baits.

Real-time crowd density estimation using images

This paper presents a technique for real-time crowd density estimation based on textures of crowd images. In this technique, the current image from a sequence of input images is classified into a crowd density class. Then, the classification is corrected by a low-pass filter based on the crowd density classification of the last n images of the input sequence. The technique obtained 73.89% of correct classification in a real-time application on a sequence of 9892 crowd images. Distributed processing was used in order to obtain real-time performance. © Springer-Verlag Berlin Heidelberg 2005.