9 resultados para Data clustering. Fuzzy C-Means. Cluster centers initialization. Validation indices
em DigitalCommons@The Texas Medical Center
Resumo:
An integrated approach for multi-spectral segmentation of MR images is presented. This method is based on the fuzzy c-means (FCM) and includes bias field correction and contextual constraints over spatial intensity distribution and accounts for the non-spherical cluster's shape in the feature space. The bias field is modeled as a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of intensity are added into the FCM cost functions. To reduce the computational complexity, the contextual regularizations are separated from the clustering iterations. Since the feature space is not isotropic, distance measure adopted in Gustafson-Kessel (G-K) algorithm is used instead of the Euclidean distance, to account for the non-spherical shape of the clusters in the feature space. These algorithms are quantitatively evaluated on MR brain images using the similarity measures.
Resumo:
Intensity non-uniformity (bias field) correction, contextual constraints over spatial intensity distribution and non-spherical cluster's shape in the feature space are incorporated into the fuzzy c-means (FCM) for segmentation of three-dimensional multi-spectral MR images. The bias field is modeled by a linear combination of smooth polynomial basis functions for fast computation in the clustering iterations. Regularization terms for the neighborhood continuity of either intensity or membership are added into the FCM cost functions. Since the feature space is not isotropic, distance measures, other than the Euclidean distance, are used to account for the shape and volumetric effects of clusters in the feature space. The performance of segmentation is improved by combining the adaptive FCM scheme with the criteria used in Gustafson-Kessel (G-K) and Gath-Geva (G-G) algorithms through the inclusion of the cluster scatter measure. The performance of this integrated approach is quantitatively evaluated on normal MR brain images using the similarity measures. The improvement in the quality of segmentation obtained with our method is also demonstrated by comparing our results with those produced by FSL (FMRIB Software Library), a software package that is commonly used for tissue classification.
Resumo:
Background: Despite almost 40 years of research into the etiology of Kawasaki Syndrome (KS), there is little research published on spatial and temporal clustering of KS cases. Previous analysis has found significant spatial and temporal clustering of cases, therefore cluster analyses were performed to substantiate these findings and provide insight into incident KS cases discharged from a pediatric tertiary care hospital. Identifying clusters from a single institution would allow for prospective analysis of risk factors and potential exposures for further insight into KS etiology. ^ Methods: A retrospective study was carried out to examine the epidemiology and distribution of patients presenting to Texas Children’s Hospital in Houston, Texas, with a diagnosis of Acute Febrile Mucocutaneous Lymph Node Syndrome (MCLS) upon discharge from January 1, 2005 to December 31, 2009. Spatial, temporal, and space-time cluster analyses were performed using the Bernoulli model with case and control event data. ^ Results: 397 of 102,761 total patients admitted to Texas Children’s Hospital had a principal or secondary diagnosis of Acute Febrile MCLS upon over the 5 year period. Demographic data for KS cases remained consistent with known disease epidemiology. Spatial, temporal, and space-time analyses of clustering using the Bernoulli model demonstrated no statistically significant clusters. ^ Discussion: Despite previous findings of spatial-temporal clustering of KS cases, there were no significant clusters of KS cases discharged from a single institution. This implicates the need for an expanded approach to conducting spatial-temporal cluster analysis and KS surveillance given the limitations of evaluating data from a single institution.^
Resumo:
Free-standing emergency centers (FECs) represent a new approach to the delivery of health care which are competing for patients with more conventional forms of ambulatory care in many parts of the U.S. Currently, little is known about these centers and their patient populations. The purpose of this study, therefore, was to describe the patients who visited two commonly-owned FECs, and determine the reasons for their visits. An economic model of the demand for FEC care was developed to test its ability to predict the economic and sociodemographic factors of use. Demand analysis of other forms of ambulatory services, such as a regular source of care (RSOC), was also conducted to examine the issues of substitution and complementarity.^ A systematic random sample was chosen from all private patients who used the clinics between July 1 and December 31, 1981. Data were obtained by means of a telephone interview and from clinic records. Five hundred fifty-one patients participated in the study.^ The typical FEC patient was a 26 year old white male with a minimum of a high school education, and a family income exceeding $25,000 a year. He had lived in the area for at least twenty years, and was a professional or a clerical worker. The patients made an average of 1.26 visits to the FECs in 1981. The majority of the visits involved a medical complaint; injuries and preventive care were the next most common reasons for visits.^ The analytic results revealed that time played a relatively important role in the demand for FEC care. As waiting time at the patients' regular source of care increased, the demand for FEC care increased, indicating that the clinic serves as a substitute for the patients' usual means of care. Age and education were inversely related to the demand for FEC care, while those with a RSOC frequented the clinics less than those lacking such a source.^ The patients used the familiar forms of ambulatory care, such as a private physician or an emergency room in a more typical fashion. These visits were directly related to the age and education of the patients, existence of a regular source of care, and disability days, which is a measure of health status. ^
Resumo:
Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^
Resumo:
The rates of syphilis in the United States have increased since the all time low in 2000. In 2003, the rates of syphilis in the United States were 2.5 cases per 100,000. There were 178 reported cases of primary and secondary syphilis (8.9 cases per 100,000) in Houston, Texas, which was a 58.9% increase from 2002. While syphilis can be completely treated now, unlike in times past, it is still a public health concern. The purpose of this study is to examine the possibility of modeling the impact of an immune response in primary and secondary syphilis in 63 major cities across the United States, stratified by gender and racial-ethnic groups. A Fourier analysis will be performed by SAS. Subsequently, this study will compare the results to a similar study of syphilis in 68 US cities, that focused on immune response, however, did not stratified by race and gender. This study will help determine if the oscillating rates of syphilis are due to biological factors of the disease or to behavioral changes in the population. This study will use surveillance data from 63 major cities across the United States. The data will be provided by the Centers of Disease Control. Ultimately, this study will expand the knowledge of the effect of immunity on endemics.^
Resumo:
This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^
Resumo:
Clostridium difficile is the leading definable cause of nosocomial diarrhea worldwide due to its virulence, multi-drug resistance, spore-forming ability, and environmental persistence. The incidence of C. difficile infection (CDI) has been increasing exponentially in the last decade. Virulent strains of C. difficile produce either toxin A and/or toxin B, which are essential for the pathogenesis of this bacterium. Current methods for diagnosing CDI are mostly qualitative tests that detect the bacterium, the toxins, or the toxin genes. These methods do not differentiate virulent C. difficile strains that produce active toxins from non-virulent strains that do not produce toxins or produce inactive toxins. Based on the knowledge that C. difficile toxins A and B cleave a substrate that is stereochemically similar to the native substrate of the toxins, uridine diphosphoglucose, a quantitative, cost-efficient assay, the Cdifftox activity assay, was developed to measure C. difficile toxin activity. The concept behind the activity assay was modified to develop a novel, rapid, sensitive, and specific assay for C. difficile toxins in the form of a selective and differential agar plate culture medium, the Cdifftox Plate assay (CDPA). This assay combines in a single step the specific identification of C. difficile strains and the detection of active toxin(s). The CDPA was determined to be extremely accurate (99.8% effective) at detecting toxin-producing strains based on the analysis of 528 C. difficile isolates selected from 50 tissue culture cytotoxicity assay-positive clinical stool samples. This new assay advances and improves the culture methodology in that only C. difficile strains will grow on this medium and virulent strains producing active toxins can be differentiated from non-virulent strains. This new method reduces the time and effort required to isolate and confirm toxin-producing C. difficile strains and provides a clinical isolate for antibiotic susceptibility testing and strain typing. The Cdifftox activity assay was used to screen for inhibitors of toxin activity. Physiological levels of the common human conjugated bile salt, taurocholate, was found to inhibit toxin A and B in vitro activities. When co-incubated ex vivo with purified toxin B, taurocholate protected Caco-2 colonic epithelial cells from the damaging effects of the toxin. Furthermore, using a caspase-3 detection assay, taurocholate reduced the extent of toxin B-induced Caco-2 cell apoptosis. These results suggest that bile salts can be effective in protecting the gut epithelium from C. difficile toxin damage, thus, the delivery of physiologic amounts of taurocholate to the colon, where it is normally in low concentration, could be useful in CDI treatment. These findings may help to explain why bile rich small intestine is spared damage in CDI, while the bile salt poor colon is vulnerable in CDI. Toxin synthesis in C. difficile occurs during the stationary phase, but little is known about the regulation of these toxins. It was hypothesized that C. difficile toxin synthesis is regulated by a quorum sensing mechanism. Two lines of evidence supported this hypothesis. First, a small (KDa), diffusible, heat-stable toxin-inducing activity accumulates in the medium of high-density C. difficile cells. This conditioned medium when incubated with low-density log-phase cells causes them to produce toxin early (2-4 hrs instead of 12-16 hrs) and at elevated levels when compared with cells grown in fresh medium. These data suggested that C. difficile cells extracellularly release an inducing molecule during growth that is able to activate toxin synthesis prematurely and demonstrates for the first time that toxin synthesis in C. difficile is regulated by quorum signaling. Second, this toxin-inducing activity was partially purified from high-density stationary-phase culture supernatant fluid by HPLC and confirmed to induce early toxin synthesis, even in C. difficile virulent strains that over-produce the toxins. Mass spectrometry analysis of the purified toxin-inducing fraction from HPLC revealed a cyclic compound with a mass of 655.8 Da. It is anticipated that identification of this toxin-inducing compound will advance our understanding of the mechanism involved in the quorum-dependent regulation of C. difficile toxin synthesis. This finding should lead to the development of even more sensitive tests to diagnose CDI and may lead to the discovery of promising novel therapeutic targets that could be harnessed for the treatment C. difficile infections.
Resumo:
Background. Injecting drug users (IDUs) are at risk of infection with Hepatitis C Virus (HCV) and Human Immunodeficiency Virus (HIV). Independently, each of these viruses is a serious threat to health, with HIV ravaging the body’s immune system, and HCV causing cirrhosis, liver cancer and liver failure. Co-infection with HIV/HCV weakens the response to antiretroviral therapy in HIV patients. IDUs with HIV/HCV co-infection are at a 20 times higher risk of having liver-related morbidity and mortality than IDUs with HIV alone. In Vietnam, studies to ascertain the prevalence of HIV have found high rates, but little is known about their HCV status. ^ Purpose. To measure the prevalence of HCV and HIV infection and identify factors associated with these viruses among IDUs at drug treatment centers in northern Vietnam. ^ Methods. A cross-sectional study was conducted from November 2007 to February 2008 with 455 injecting drug users aged 18 to 39 years, admitted no more than two months earlier to one of four treatment centers in Northern Vietnam (Hatay Province) (response rate=95%). Participants, all of whom had completed detoxification and provided informed consent, completed a risk assessment questionnaire and had their blood drawn to test for the presence of antibody-HCV and antibody-HIV with enzyme immuno assays. Univariate and multivariable logistic regression models were utilized to explore the strength of association using HIV, HCV infections and HIV/HCV co-infection as outcomes and demographic characteristics, drug use and sexual behaviors as factors associated with these outcomes. Unadjusted and adjusted odds ratios and 95% confidence intervals were calculated. ^ Results. Among all IDU study participants, the prevalence of HCV alone was 76.9%, HIV alone was 19.8%. The prevalence of HIV/HCV co-infection was 92.2% of HIV-positive and 23.7% of HCV-positive respondents. No sexual risk behaviors for lifetime, six months or 30 days prior to admission were significantly associated with HCV or HIV infection among these IDUs. Only duration of injection drug use was independently associated with HCV and HIV infection, respectively. Longer duration was associated with higher prevalence. Nevertheless, while HCV infection among IDUs who reported being in their first year of injecting drugs were lower than longer time injectors, their rates were still substantial, 67.5%. ^ Compared with either HCV mono-infection or HIV/HCV non-infection, HIV/HCV co-infection was associated with the length of drug injection history but was not associated with sexual behaviors. Higher education was associated with a lower prevalence of HIV/HCV co-infection. When compared with HIV/HCV non-infection, current marriage was associated with a lower prevalence of HIV/HCV co-infection. ^ Conclusions. HCV was prevalent among IDUs from 18 to 39 years old at four drug treatment centers in northern Vietnam. Co-infection with HCV was predominant among HIV-positive IDUs. HCV and HIV co-infection were closely associated with the length of injection drug history. Further research regarding HCV/HIV co-infection should include non-injecting drug users to assess the magnitude of sexual risk behaviors on HIV and HCV infection. (At these treatment centers non-IDUs constituted 10-20% of the population.) High prevalence of HCV prevalence among IDUs, especially among HIV-infected IDUs, suggests that drug treatment centers serving IDUs should include not only HIV prevention education but they should also include the prevention of viral hepatitis. In addition, IDUs who are HIV-positive need to be tested for HCV to receive the best course of therapy and achieve the best response to HIV treatment. These data also suggest that because many IDUs get infected with HCV in the first year of their injection drug career, and because they also engaged in high risk sexual behaviors, outreach programs should focus on harm reduction, safer drug use and sexual practices to prevent infection among drug users who have not yet begun injecting drugs and to prevent further spread of HCV, HIV and co-infection. ^