Patient admission prediction using a pruned fuzzy min–max neural network with rule extraction

A useful patient admission prediction model that helps the emergency department of a hospital admit patients efficiently is of great importance. It not only improves the care quality provided by the emergency department but also reduces waiting time of patients. This paper proposes an automatic prediction method for patient admission based on a fuzzy min–max neural network (FMM) with rules extraction. The FMM neural network forms a set of hyperboxes by learning through data samples, and the learned knowledge is used for prediction. In addition to providing predictions, decision rules are extracted from the FMM hyperboxes to provide an explanation for each prediction. In order to simplify the structure of FMM and the decision rules, an optimization method that simultaneously maximizes prediction accuracy and minimizes the number of FMM hyperboxes is proposed. Specifically, a genetic algorithm is formulated to find the optimal configuration of the decision rules. The experimental results using a large data set consisting of 450740 real patient records reveal that the proposed method achieves comparable or even better prediction accuracy than state-of-the-art classifiers with the additional ability to extract a set of explanatory rules to justify its predictions.

Ipoll: Automatic polling using online search

For years, opinion polls rely on data collected through telephone or person-to-person surveys. The process is costly, inconvenient, and slow. Recently online search data has emerged as potential proxies for the survey data. However considerable human involvement is still needed for the selection of search indices, a task that requires knowledge of both the target issue and how search terms are used by the online community. The robustness of such manually selected search indices can be questionable. In this paper, we propose an automatic polling system through a novel application of machine learning. In this system, the needs for examining, comparing, and selecting search indices have been eliminated through automatic generation of candidate search indices and intelligent combination of the indices. The results include a publicly accessible web application that provides real-time, robust, and accurate measurements of public opinions on several subjects of general interest.

Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

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

Off line extraction of phenol from human urine sample with isoamyl alcohol and determination by HPLC

This method has been developed for extraction and determination of phenol in a urine sample by high performance liquid chromatography.After acid hydrolysis, the free phenol was extracted with isoamyl alcohol solvent, followed by back extraction with 0.5 mol.L-1 sodium hydroxide solution and analyzed by an isocratic HPLC Varian System, equipped with reverse-phase column (MicroPak-C-18). The mobile phase was acetonitrile in 0.01 mol.L-1 hydrochloric acid solution, (20:80 v/v), and at a now-rate of 1.0 mL.min-1. The chromatogram was monitored at 220 nm in room temperature. The identification was based on retention time and the quantification was performed by automatic peak-area determination, corrected for the external standards method.The recovery was higher than 99.5 % for phenol and reproducibility of method was shown to be 2.3% standard deviation and 5.6% coefficient of variance (n=20). The limit detection was 0.05 mgL(-1) and a range of 0.05 to 20.0 mgL(-1) of phenol for linearity.

Short-term vs long-term calcium hydroxide therapy after immediate tooth replantation: a histomorphometric study in monkey's teeth

Endodontic treatment is an important step of tooth replantation protocols, but the ideal moment for definitive obturation of replanted teeth has not yet been established. In this study, a histomorphometric analysis was undertaken to evaluate the repair process on immediate replantation of monkeys teeth after calcium hydroxide (CH) therapy for 1 and 6 months followed by root canal filling with a CH-based sealer (Sealapex (R)). The maxillary and mandibular lateral incisors of five female Cebus apella monkeys were extracted, kept in sterile saline for 15 min, replanted and splinted with stainless steel orthodontic wire and composite resin for 10 days. In Group I (control), definitive root canal filling was performed before tooth extraction. In Groups II and III, CH therapy started after removal of splint, and definitive root canal filling was performed 1 and 6 months later, respectively. The animals were euthanized 9 months after replantation, and specimens were processed for histomorphometric analysis. In all groups, epithelial attachment occurred at the cementoenamel junction or very close to this region; the areas of resorption on root surface had small extension and depth and were repaired by newly formed cementum; and the periodontal ligament was organized. Statistical analysis of the scores obtained for the histomorphometric parameters did not show any statistically significant difference (P = 0.1221) among the groups. The results suggests that when endodontic treatment is initiated 10 days after immediate replantation and an antibiotic regimen is associated, definitive root canal filling can be performed after a short-term CH therapy.

Long-term treatment with alendronate increases the surgical difficulty during simple exodontias - an in vivo observation in Holtzman rats

Background: Atraumatic teeth extractions protocols are highly encouraged in patients taking bisphosphonates (Bps) to reduce surgical trauma and, consequently, the risk of jaws osteonecrosis development. In this way, this paper aims to report the findings of increased surgical difficulty during simple exodontias in animals treated with bisphosphonates.Methods: Sixty male Holtzman rats were randomly distributed into three groups of 20 animals and received daily subcutaneous administration of 1 mg/kg (AL1) or 3 mg/kg (AL3) of alendronate or saline solution (CTL). After 60 days of drug therapy all animals were submitted to first lower molars extractions under general anesthesia. Operatory surgical time and the frequency of teeth fractures were measured as principal outcomes and indicators of surgical difficulty degree.Results: Animals treated with alendronate (AL1 and AL3) were associated to higher operatory times and increased frequency of teeth fractures compared to match controls.Conclusions: The bisphosphonate therapy may be associated with an increased surgical difficulty and trauma following simple exodontias protocols, which is considered a critical issue when it comes to osteonecrosis development.

Long-term effects of developmental exposure to di-n-butyl-phthalate (DBP) on rat prostate: Proliferative and inflammatory disorders and a possible role of androgens

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

On-line extraction and determination of carbofuran in raw milk by direct HPLC injection on an ISRP column

A method has been developed for extraction and determination of carbofuran in milk. The method involved direct injection of raw milk on to a human serum albumin dimethyloctyl-silica gel (HSA-Cs) column and the use of 80:20 (v/v) 0.01 M phosphate buffer pH 5.5 - acetonitrile as mobile phase. UV spectrophotometric detection was performed at 220 nm. Identification was based on retention time. Quantification was performed by automatic peak-area determination and was calibrated by use of an external standard.

Georeferenced road extraction and formulation of hypotheses for new road segments

The acquisition and update of Geographic Information System (GIS) data are typically carried out using aerial or satellite imagery. Since new roads are usually linked to georeferenced pre-existing road network, the extraction of pre-existing road segments may provide good hypotheses for the updating process. This paper addresses the problem of extracting georeferenced roads from images and formulating hypotheses for the presence of new road segments. Our approach proceeds in three steps. First, salient points are identified and measured along roads from a map or GIS database by an operator or an automatic tool. These salient points are then projected onto the image-space and errors inherent in this process are calculated. In the second step, the georeferenced roads are extracted from the image using a dynamic programming (DP) algorithm. The projected salient points and corresponding error estimates are used as input for this extraction process. Finally, the road center axes extracted in the previous step are analyzed to identify potential new segments attached to the extracted, pre-existing one. This analysis is performed using a combination of edge-based and correlation-based algorithms. In this paper we present our approach and early implementation results.

Semi-automatic modeling of buildings from digital surface models

Semi-automatic building detection and extraction is a topic of growing interest due to its potential application in such areas as cadastral information systems, cartographic revision, and GIS. One of the existing strategies for building extraction is to use a digital surface model (DSM) represented by a cloud of known points on a visible surface, and comprising features such as trees or buildings. Conventional surface modeling using stereo-matching techniques has its drawbacks, the most obvious being the effect of building height on perspective, shadows, and occlusions. The laser scanner, a recently developed technological tool, can collect accurate DSMs with high spatial frequency. This paper presents a methodology for semi-automatic modeling of buildings which combines a region-growing algorithm with line-detection methods applied over the DSM.

Automated extraction of road network from medium-and high-resolution images

This paper presents an automatic methodology for road network extraction from medium-and high-resolution aerial images. It is based on two steps. In the first step, the road seeds (i.e., road segments) are extracted using a set of four road objects and another set of connection rules among road objects. Each road object is a local representation of an approximately straight road fragment and its construction is based on a combination of polygons describing all relevant image edges, according to some rules embodying road knowledge. Each road seed is composed by a sequence of connected road objects in which each sequence of this type can be geometrically structured as a chain of contiguous quadrilaterals. In the second step, two strategies for road completion are applied in order to generate the complete road network. The first strategy is based on two basic perceptual grouping rules, i.e., proximity and collinearity rules, which allow the sequential reconstruction of gaps between every pair of disconnected road segments. This strategy does not allow the reconstruction of road crossings, but it allows the extraction of road centerlines from the contiguous quadrilaterals representing connected road segments. The second strategy for road completion aims at reconstructing road crossings. Firstly, the road centerlines are used to find reference points for road crossings, which are their approximate positions. Then these points are used to extract polygons representing the contours of road crossings. This paper presents the proposed methodology and experimental results. © Pleiades Publishing, Inc. 2006.

Methodology for automatic selection of passes in surface grinding

The main purpose of this work is the development of computational tools in order to assist the on-line automatic detection of burn in the surface grinding process. Most of the parameters currently employed in the burning recognition (DPO, FKS, DPKS, DIFP, among others) do not incorporate routines for automatic selection of the grinding passes, therefore, requiring the user's interference for the choice of the active region. Several methods were employed in the passes extraction; however, those with the best results are presented in this article. Tests carried out in a surface-grinding machine have shown the success of the algorithms developed for pass extraction. Copyright © 2007 by ABCM.

Oral myofunctional and electromyographic evaluation of the anterior suprahyoid muscles and tongue thrust in patients with class II/1 malocclusion submitted to first premolar extraction

Objective: The aim of this study was to assess the existence of myofunctional alterations before and after first premolar extraction in Class II/1 malocclusion patients that could endanger the long-term dental arch stability. Materials and Methods: The study was performed by means of morphological, functional and electromyographic analyses in 17 Class II/1 malocclusion patients (group T) and 17 Class I malocclusion patients (group C), both groups with 12-30-year age range (mean age: 20.93 ± 4.94 years). Results: Data analyzed statistically by Student's t-test showed a significant decrease in the maxillary and mandibular dental arch perimeters after orthodontic treatment (p<0.05). The Kruskal-Wallis test analyzed data from tongue posture at rest and during swallowing, not showing significant differences after treatment (groups Tb and Ta) (p>0.05). However, group T differed significantly from group C (p<0.05). The electromyographic data showed that the anterior right and left suprahyoid muscles acted synergistically in both groups, while having a lower myoelectric activity in group T during swallowing. Conclusions: Myofunctional alterations observed after the orthodontic treatment in Class II/1 malocclusion seemed to jeopardize the long-term orthodontic stability, making recurrence possible. Further research should be conducted to compare electromyographic data before and after orthodontic treatment in order to corroborate the results of the present investigation.

Automatic segmentation of digital images applied in cardiac medical images

The digital image processing has been applied in several areas, especially where it is necessary use tools for feature extraction and to get patterns of the studied images. In an initial stage, the segmentation is used to separate the image in parts that represents a interest object, that may be used in a specific study. There are several methods that intends to perform such task, but is difficult to find a method that can easily adapt to different type of images, that often are very complex or specific. To resolve this problem, this project aims to presents a adaptable segmentation method, that can be applied to different type of images, providing an better segmentation. The proposed method is based in a model of automatic multilevel thresholding and considers techniques of group histogram quantization, analysis of the histogram slope percentage and calculation of maximum entropy to define the threshold. The technique was applied to segment the cell core and potential rejection of tissue in myocardial images of biopsies from cardiac transplant. The results are significant in comparison with those provided by one of the best known segmentation methods available in the literature. © 2010 IEEE.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.