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Testing Samples (testing + sample)
Selected AbstractsAssessment of Individual Risk of Death Using Self-Report Data: An Artificial Neural Network Compared with a Frailty IndexJOURNAL OF AMERICAN GERIATRICS SOCIETY, Issue 7 2004Xiaowei Song PhD Objectives: To evaluate the potential of an artificial neural network (ANN) in predicting survival in elderly Canadians, using self-report data. Design: Cohort study with up to 72 months follow-up. Setting: Forty self-reported characteristics were obtained from the community sample of the Canadian Study of Health and Aging. An individual frailty index score was calculated as the proportion of deficits experienced. For the ANN, randomly selected participants formed the training sample to derive relationships between the variables and survival and the validation sample to control overfitting. An ANN output was generated for each subject. A separate testing sample was used to evaluate the accuracy of prediction. Participants: A total of 8,547 Canadians aged 65 to 99, of whom 1,865 died during 72 months of follow-up. Measurements: The output of an ANN model was compared with an unweighted frailty index in predicting survival patterns using receiver operating characteristic (ROC) curves. Results: The area under the ROC curve was 86% for the ANN and 62% for the frailty index. At the optimal ROC value, the accuracy of the frailty index was 70.0%. The ANN accuracy rate over 10 simulations in predicting the probability of individual survival mean±standard deviation was 79.2±0.8%. Conclusion: An ANN provided more accurate survival classification than an unweighted frailty index. The data suggest that the concept of biological redundancy might be operationalized from health survey data. [source] Aspects of Left Ventricular Morphology Outperform Left Ventricular Mass for Prediction of QRS DurationANNALS OF NONINVASIVE ELECTROCARDIOLOGY, Issue 2 2010Nina Hakacova M.D., Ph.D. Background: The knowledge of the case-specific normal QRS duration in each individual is needed when determining the onset, severity and progression of the heart disease. However, large interindividual variability even of the normal QRS duration exists. The aims of the study were to develop a model for prediction of normal QRS complex duration and to test it on healthy individuals. Methods: The study population of healthy adult volunteers was divided into a sample for development of a prediction model (n = 63) and a testing sample (n = 30). Magnetic resonance imaging data were used to assess anatomical characteristics of the left ventricle: the angle between papillary muscles (PMA), the length of the left ventricle (LVL) and left ventricular mass (LVM). Twelve-lead electrocardiogram (ECG) was used for measurement of the QRS duration. Multiple linear regression analysis was used to develop a prediction model to estimate the QRS duration. The accuracy of the prediction model was assessed by comparing predicted with measured QRS duration in the test set. Results: The angle between PMA and the length of the LVL were statistically significant predictors of QRS duration. Correlation between QRS duration and PMA and LVL was r = 0.57, P = 0.0001 and r = 0.45, P = 0.0002, respectively. The final model for prediction of the QRS was: QRSPredicted= 97 + (0.35 × LVL) , (0.45 × PMA). The predicted and real QRS duration differed with median 1 ms. Conclusions: The model for prediction of QRS duration opens the ability to predict case-specific normal QRS duration. This knowledge can have clinical importance, when determining the normality on case-specific basis. Ann Noninvasive Electrocardiol 2010;15(2):124,129 [source] ,-Cyclodextrin as novel chiral probe for enantiomeric separation by electromigration methodsELECTROPHORESIS, Issue 21 2006Dorothee Wistuba Abstract Native ,-CD has been employed as chiral selector in CE and MEKC. To investigate the potential of the enantiodiscriminating properties of ,-CD, negatively charged 5-dimethylamino-1-naphthalene-sulfonyl (dansyl)-, 2,4-dinitrophenyl (DNP)- and FMOC-derivatives of several amino acids, 1,1'-binaphthyl-2,2'-diylhydrogenphosphate, flavanones and three positively charged drugs have been selected as testing samples. Enantioresolution factors up to 4.82 have been observed. The results were compared with those achieved by the conventional running buffer additives ,-, ,- and ,-CDs. For several examples a steady increase of enantioresolution with increasing degree of oligomerization has been detected. [source] Prediction of interactiveness between small molecules and enzymes by combining gene ontology and compound similarityJOURNAL OF COMPUTATIONAL CHEMISTRY, Issue 8 2010Lei Chen Abstract Determination of whether a small organic molecule interacts with an enzyme can help to understand the molecular and cellular functions of organisms, and the metabolic pathways. In this research, we present a prediction model, by combining compound similarity and enzyme similarity, to predict the interactiveness between small molecules and enzymes. A dataset consisting of 2859 positive couples of small molecule and enzyme and 286,056 negative couples was employed. Compound similarity is a measurement of how similar two small molecules are, proposed by Hattori et al., J Am Chem Soc 2003, 125, 11853 which can be availed at http://www.genome.jp/ligand-bin/search_compound, while enzyme similarity was obtained by three ways, they are blast method, using gene ontology items and functional domain composition. Then a new distance between a pair of couples was established and nearest neighbor algorithm (NNA) was employed to predict the interactiveness of enzymes and small molecules. A data distribution strategy was adopted to get a better data balance between the positive samples and the negative samples during training the prediction model, by singling out one-fourth couples as testing samples and dividing the rest data into seven training datasets,the rest positive samples were added into each training dataset while only the negative samples were divided. In this way, seven NNAs were built. Finally, simple majority voting system was applied to integrate these seven models to predict the testing dataset, which was demonstrated to have better prediction results than using any single prediction model. As a result, the highest overall prediction accuracy achieved 97.30%. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010 [source] Relationship between scale effect and structure levels in fibrous structuresPOLYMER COMPOSITES, Issue 2 2000Ning Pan A series of testing samples of fibers, yarns, fabrics, and coated fabrics of the same source were prepared and then tested at constant strain rate but different gauge lengths on an Instron tester for tensile test. The results are compared to see the scale effect at different structure levels of fibrous materials. Discussions and explanations of the data are provided as well. [source] Character of the Si and Al Phases in Coal Gangue and Its AshACTA GEOLOGICA SINICA (ENGLISH EDITION), Issue 6 2009WANG Lihua Abstract: Analysis of the Si and Al phases in coal gangue fuel and its ash is important for use of coal gangue ashes. A comprehensive study by theoretical and experimental analyses with differential thermal analysis, X-ray diffraction and Infrared Spectroscopy has been made in the present article to explore the diagram of the Si and Al phases in coal gangue fuel and its ashes. It is found that kaolinite and quartz are the main phases in coal gangue fuel. The ratio of moles Al2O3to SiO2 (i.e., Al2O3 (mole)/ SiO2 (mole)) is usually no more than 0.5 in most coal gangue fuel and its ashes. The kaolinit at about 984°C releases a large quantity of SiO2, which makes calcine coal gangue more active than coal gangue itself. The relationship between the ratio Al2O3 (mole)/SiO2 (mole) and the components of coal gangue ash is analyzed, resulting in a formula to calculate the quantity of each phase. Applying the formula to the testing samples from an electric plant in north China supports the above conclusions. [source] | ||||||||||