979 resultados para Text classification
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This atlas presents a comprehensive set of thematic maps depicting a wide range of aspects of the Songwe river area. It includes baseline maps (such as topographic overview, hillshade), satellite images (years 1991, 2001, 2004), land cover and land cover change, biomass and biomass change, priority conservation areas, resource management (watershed classification, watershed classification combined with biomass, soil erosion), accessibility and special maps (such as historical river course). Map clippings of the most important maps facilitate the readability of the maps. The accompanying explanatory text sheets contain graphics and information about material, methods, results and interpretation.
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Background and purpose: Breast cancer continues to be a health problem for women, representing 28 percent of all female cancers and remaining one of the leading causes of death for women. Breast cancer incidence rates become substantial before the age of 50. After menopause, breast cancer incidence rates continue to increase with age creating a long-lasting source of concern (Harris et al., 1992). Mammography, a technique for the detection of breast tumors in their nonpalpable stage when they are most curable, has taken on considerable importance as a public health measure. The lifetime risk of breast cancer is approximately 1 in 9 and occurs over many decades. Recommendations are that screening be periodic in order to detect cancer at early stages. These recommendations, largely, are not followed. Not only are most women not getting regular mammograms, but this circumstance is particularly the case among older women where regular mammography has been proven to reduce mortality by approximately 30 percent. The purpose of this project was to increase our understanding of factors that are associated with stage of readiness to obtain subsequent mammograms. A secondary purpose of this research was to suggest further conceptual considerations toward the extension of the Transtheoretical Model (TTM) of behavior change to repeat screening mammography. ^ Methods. A sample (n = 1,222) of women 50 years and older in a large multi-specialty clinic in Houston, Texas was surveyed by mail questionnaire regarding their previous screening experience and stage of readiness to obtain repeat screening. A computerized database, maintained on all women who undergo mammography at the clinic, was used to identify women who are eligible for the project. The major statistical technique employed to select the significant variables and to examine the man and interaction effects of independent variables on dependent variables was polychotomous stepwise, logistic regression. A prediction model for each stage of readiness definition was estimated. The expected probabilities for stage of readiness were calculated to assess the magnitude and direction of significant predictors. ^ Results. Analysis showed that both ways of defining stage of readiness for obtaining a screening mammogram were associated with specific constructs, including decisional balance and processes of the change. ^ Conclusions. The results of the present study demonstrate that the TTM appears to translate to repeat mammography screening. Findings in the current study also support finding of previous studies that suggest that stage of readiness is associated with respondent decisional balance and the processes of change. ^
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The presence of outlying anchor items is an issue faced by many testing agencies. This study examines the effect of removing or retaining one aberrant anchor item. The degree of aberrancy was manipulated as well as the ability distribution of examinees, and four IRT scaling methods were investigated (Mean-sigma, mean-mean, Stocking & Lord, and Haebara). The results indicate that the percent of correctly classified students was not affected by either retaining or removing the aberrant item, although the over- and under- classification of examinees was. There was no difference among the methods.
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It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.
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Cervical cancer is the leading cause of death and disease from malignant neoplasms among women in developing countries. Even though the Pap smear has significantly decreased the number of deaths from cervical cancer in the past years, it has its limitations. Researchers have developed an automated screening machine which can potentially detect abnormal cases that are overlooked by conventional screening. The goal of quantitative cytology is to classify the patient's tissue sample based on quantitative measurements of the individual cells. It is also much cheaper and potentially can take less time. One of the major challenges of collecting cells with a cytobrush is the possibility of not sampling any existing dysplastic cells on the cervix. Being able to correctly classify patients who have disease without the presence of dysplastic cells could improve the accuracy of quantitative cytology algorithms. Subtle morphologic changes in normal-appearing tissues adjacent to or distant from malignant tumors have been shown to exist, but a comparison of various statistical methods, including many recent advances in the statistical learning field, has not previously been done. The objective of this thesis is to use different classification methods applied to quantitative cytology data for the detection of malignancy associated changes (MACs). In this thesis, Elastic Net is the best algorithm. When we applied the Elastic Net algorithm to the test set, we combined the training set and validation set as "training" set and used 5-fold cross validation to choose the parameter for Elastic Net. It has a sensitivity of 47% at 80% specificity, an AUC 0.52, and a partial AUC 0.10 (95% CI 0.09-0.11).^
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Sea floor morphology plays an important role in many scientific disciplines such as ecology, hydrology and sedimentology since geomorphic features can act as physical controls for e.g. species distribution, oceanographically flow-path estimations or sedimentation processes. In this study, we provide a terrain analysis of the Weddell Sea based on the 500 m × 500 m resolution bathymetry data provided by the mapping project IBCSO. Seventeen seabed classes are recognized at the sea floor based on a fine and broad scale Benthic Positioning Index calculation highlighting the diversity of the glacially carved shelf. Beside the morphology, slope, aspect, terrain rugosity and hillshade were calculated. Applying zonal statistics to the geomorphic features identified unambiguously the shelf edge of the Weddell Sea with a width of 45-70 km and a mean depth of about 1200 m ranging from 270 m to 4300 m. A complex morphology of troughs, flat ridges, pinnacles, steep slopes, seamounts, outcrops, and narrow ridges, structures with approx. 5-7 km width, build an approx. 40-70 km long swath along the shelf edge. The study shows where scarps and depressions control the connection between shelf and abyssal and where high and low declination within the scarps e.g. occur. For evaluation purpose, 428 grain size samples were added to the seabed class map. The mean values of mud, sand and gravel of those samples falling into a single seabed class was calculated, respectively, and assigned to a sediment texture class according to a common sediment classification scheme.