The Experts below are selected from a list of 281181 Experts worldwide ranked by ideXlab platform
Christopher Jermaine - One of the best experts on this subject based on the ideXlab platform.
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Online Random Shuffling of Large Database Tables
IEEE Transactions on Knowledge and Data Engineering, 2007Co-Authors: Christopher JermaineAbstract:Many applications require a randomized ordering of input data. Examples include algorithms for online aggregation, data mining, and various randomized algorithms. Most existing work seems to assume that accessing the records from a Large Database in a randomized order is not a difficult problem. However, it turns out to be extremely difficult in practice. Using existing methods, randomization is either extremely expensive at the front end (as data are loaded), or at the back end (as data are queried). This paper presents a simple file structure which supports both efficient, online random shuffling of a Large Database, as well as efficient online sampling or randomization of the Database when it is queried. The key innovation of our method is the introduction of a small degree of carefully controlled, rigorously monitored nonrandomness into the file
Mohamed B. Elshazly - One of the best experts on this subject based on the ideXlab platform.
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patient level discordance in population percentiles of the total cholesterol to high density lipoprotein cholesterol ratio in comparison with low density lipoprotein cholesterol and non high density lipoprotein cholesterol the very Large Database of
Circulation, 2015Co-Authors: Mohamed B. Elshazly, Peter P. Toth, Erin D. Michos, Renato Quispe, Allan D Sniderman, Maciej Banach, Krishnaji R Kulkarni, Josef Coresh, Roger S Blumenthal, Steven R JonesAbstract:Background—The total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, estimated low-density lipoprotein cholesterol (LDL-C), and non–HDL-C are routinely available from the standard lipid profile. We aimed to assess the extent of patient-level discordance of TC/HDL-C with LDL-C and non–HDL-C, because discordance suggests the possibility of additional information. Methods and Results—We compared population percentiles of TC/HDL-C, Friedewald-estimated LDL-C, and non–HDL-C in 1 310 432 US adults from the Very Large Database of Lipids. Lipid testing was performed by ultracentrifugation (Vertical Auto Profile, Atherotech, AL). One in 3 patients had ≥25 percentile units discordance between TC/HDL-C and LDL-C, whereas 1 in 4 had ≥25 percentile units discordance between TC/HDL-C and non–HDL-C. The proportion of patients with TC/HDL-C > LDL-C by ≥25 percentile units increased from 3% at triglycerides non–HDL-C ...
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patient level discordance in population percentiles of the total cholesterol to high density lipoprotein cholesterol ratio in comparison with low density lipoprotein cholesterol and non high density lipoprotein cholesterol the very Large Database of
Circulation, 2015Co-Authors: Peter P. Toth, Mohamed B. Elshazly, Erin D. Michos, Renato Quispe, Allan D Sniderman, Maciej Banach, Krishnaji R Kulkarni, Josef CoreshAbstract:Background— The total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, estimated low-density lipoprotein cholesterol (LDL-C), and non–HDL-C are routinely available from the standard lipid profile. We aimed to assess the extent of patient-level discordance of TC/HDL-C with LDL-C and non–HDL-C, because discordance suggests the possibility of additional information. Methods and Results— We compared population percentiles of TC/HDL-C, Friedewald-estimated LDL-C, and non–HDL-C in 1 310 432 US adults from the Very Large Database of Lipids. Lipid testing was performed by ultracentrifugation (Vertical Auto Profile, Atherotech, AL). One in 3 patients had ≥25 percentile units discordance between TC/HDL-C and LDL-C, whereas 1 in 4 had ≥25 percentile units discordance between TC/HDL-C and non–HDL-C. The proportion of patients with TC/HDL-C > LDL-C by ≥25 percentile units increased from 3% at triglycerides non–HDL-C discordance by ≥25 percentile units increased from 6% to 21%. In those with 86% of the variance in percentile discordance between TC/HDL-C versus LDL-C and non–HDL-C. Conclusions— In this contemporary, cross-sectional, big data analysis of US adults who underwent advanced lipid testing, the extent of patient-level discordance suggests that TC/HDL-C may offer potential additional information to LDL-C and non–HDL-C. Future studies are required to determine the clinical implications of this observation. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT01698489.
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patient level discordance in population percentiles of the tc hdl c ratio compared with ldl c and non hdl c the very Large Database of lipids study vldl 2b
Circulation, 2015Co-Authors: Mohamed B. Elshazly, Peter P. Toth, Erin D. Michos, Renato Quispe, Allan D Sniderman, Maciej Banach, Krishnaji R Kulkarni, Josef Coresh, Roger S Blumenthal, Steven R JonesAbstract:Background —The total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, estimated low-density lipoprotein cholesterol (LDL-C), and non-HDL-C are routinely available from the standard lipid profile. We aimed to assess the extent of patient-level discordance of TC/HDL-C with LDL-C and non-HDL-C because discordance suggests the possibility of additional information. Methods and Results —We compared population percentiles of TC/HDL-C, Friedewald-estimated LDL-C, and non-HDL-C in 1,310,432 U.S. adults from the Very Large Database of Lipids. Lipid testing was performed by ultracentrifugation (VAP, Atherotech, AL). One in three patients had ≥25 percentile units discordance between TC/HDL-C and LDL-C while one in four had ≥25 percentile units discordance between TC/HDL-C and non-HDL-C. The proportion of patients with TC/HDL-C > LDL-C by ≥25 percentile units increased from 3% at triglycerides non-HDL-C discordance by ≥25 percentile units increased from 6% to 21%. In those with 86% of the variance in percentile discordance between TC/HDL-C vs. LDL-C and non-HDL-C. Conclusions —In this contemporary, cross-sectional, big data analysis of U.S. adults who underwent advanced lipid testing, the extent of patient-level discordance suggests that TC/HDL-C may offer potential additional information to LDL-C and non-HDL-C. Future studies are required to determine the clinical implications of this observation. Clinical Trial Registration Information —www.clinicaltrials.gov. Identifier: [NCT01698489][1]. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01698489&atom=%2Fcirculationaha%2Fearly%2F2015%2F07%2F02%2FCIRCULATIONAHA.115.016163.atom
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Very Large Database of Lipids: Rationale and Design
Clinical cardiology, 2013Co-Authors: Seth S. Martin, Michael J. Blaha, Peter P. Toth, Parag H. Joshi, John W. Mcevoy, Haitham M. Ahmed, Mohamed B. Elshazly, Kristopher J. Swiger, Erin D. Michos, Peter O. KwiterovichAbstract:Blood lipids have major cardiovascular and public health implications. Lipid-lowering drugs are prescribed based in part on categorization of patients into normal or abnormal lipid metabolism, yet relatively little emphasis has been placed on: (1) the accuracy of current lipid measures used in clinical practice, (2) the reliability of current categorizations of dyslipidemia states, and (3) the relationship of advanced lipid characterization to other cardiovascular disease biomarkers. To these ends, we developed the Very Large Database of Lipids (NCT01698489), an ongoing Database protocol that harnesses deidentified data from the daily operations of a commercial lipid laboratory. The Database includes individuals who were referred for clinical purposes for a Vertical Auto Profile (Atherotech Inc., Birmingham, AL), which directly measures cholesterol concentrations of low-density lipoprotein, very low-density lipoprotein, intermediate-density lipoprotein, high-density lipoprotein, their subclasses, and lipoprotein(a). Individual Very Large Database of Lipids studies, ranging from studies of measurement accuracy, to dyslipidemia categorization, to biomarker associations, to characterization of rare lipid disorders, are investigator-initiated and utilize peer-reviewed statistical analysis plans to address a priori hypotheses/aims. In the first Database harvest (Very Large Database of Lipids 1.0) from 2009 to 2011, there were 1 340 614 adult and 10 294 pediatric patients; the adult sample had a median age of 59 years (interquartile range, 49–70 years) with even representation by sex. Lipid distributions closely matched those from the population-representative National Health and Nutrition Examination Survey. The second harvest of the Database (Very Large Database of Lipids 2.0) is underway. Overall, the Very Large Database of Lipids Database provides an opportunity for collaboration and new knowledge generation through careful examination of granular lipid data on a Large scale.
Peter P. Toth - One of the best experts on this subject based on the ideXlab platform.
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patient level discordance in population percentiles of the total cholesterol to high density lipoprotein cholesterol ratio in comparison with low density lipoprotein cholesterol and non high density lipoprotein cholesterol the very Large Database of
Circulation, 2015Co-Authors: Mohamed B. Elshazly, Peter P. Toth, Erin D. Michos, Renato Quispe, Allan D Sniderman, Maciej Banach, Krishnaji R Kulkarni, Josef Coresh, Roger S Blumenthal, Steven R JonesAbstract:Background—The total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, estimated low-density lipoprotein cholesterol (LDL-C), and non–HDL-C are routinely available from the standard lipid profile. We aimed to assess the extent of patient-level discordance of TC/HDL-C with LDL-C and non–HDL-C, because discordance suggests the possibility of additional information. Methods and Results—We compared population percentiles of TC/HDL-C, Friedewald-estimated LDL-C, and non–HDL-C in 1 310 432 US adults from the Very Large Database of Lipids. Lipid testing was performed by ultracentrifugation (Vertical Auto Profile, Atherotech, AL). One in 3 patients had ≥25 percentile units discordance between TC/HDL-C and LDL-C, whereas 1 in 4 had ≥25 percentile units discordance between TC/HDL-C and non–HDL-C. The proportion of patients with TC/HDL-C > LDL-C by ≥25 percentile units increased from 3% at triglycerides non–HDL-C ...
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patient level discordance in population percentiles of the total cholesterol to high density lipoprotein cholesterol ratio in comparison with low density lipoprotein cholesterol and non high density lipoprotein cholesterol the very Large Database of
Circulation, 2015Co-Authors: Peter P. Toth, Mohamed B. Elshazly, Erin D. Michos, Renato Quispe, Allan D Sniderman, Maciej Banach, Krishnaji R Kulkarni, Josef CoreshAbstract:Background— The total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, estimated low-density lipoprotein cholesterol (LDL-C), and non–HDL-C are routinely available from the standard lipid profile. We aimed to assess the extent of patient-level discordance of TC/HDL-C with LDL-C and non–HDL-C, because discordance suggests the possibility of additional information. Methods and Results— We compared population percentiles of TC/HDL-C, Friedewald-estimated LDL-C, and non–HDL-C in 1 310 432 US adults from the Very Large Database of Lipids. Lipid testing was performed by ultracentrifugation (Vertical Auto Profile, Atherotech, AL). One in 3 patients had ≥25 percentile units discordance between TC/HDL-C and LDL-C, whereas 1 in 4 had ≥25 percentile units discordance between TC/HDL-C and non–HDL-C. The proportion of patients with TC/HDL-C > LDL-C by ≥25 percentile units increased from 3% at triglycerides non–HDL-C discordance by ≥25 percentile units increased from 6% to 21%. In those with 86% of the variance in percentile discordance between TC/HDL-C versus LDL-C and non–HDL-C. Conclusions— In this contemporary, cross-sectional, big data analysis of US adults who underwent advanced lipid testing, the extent of patient-level discordance suggests that TC/HDL-C may offer potential additional information to LDL-C and non–HDL-C. Future studies are required to determine the clinical implications of this observation. Clinical Trial Registration— URL: http://www.clinicaltrials.gov. Unique identifier: NCT01698489.
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patient level discordance in population percentiles of the tc hdl c ratio compared with ldl c and non hdl c the very Large Database of lipids study vldl 2b
Circulation, 2015Co-Authors: Mohamed B. Elshazly, Peter P. Toth, Erin D. Michos, Renato Quispe, Allan D Sniderman, Maciej Banach, Krishnaji R Kulkarni, Josef Coresh, Roger S Blumenthal, Steven R JonesAbstract:Background —The total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio, estimated low-density lipoprotein cholesterol (LDL-C), and non-HDL-C are routinely available from the standard lipid profile. We aimed to assess the extent of patient-level discordance of TC/HDL-C with LDL-C and non-HDL-C because discordance suggests the possibility of additional information. Methods and Results —We compared population percentiles of TC/HDL-C, Friedewald-estimated LDL-C, and non-HDL-C in 1,310,432 U.S. adults from the Very Large Database of Lipids. Lipid testing was performed by ultracentrifugation (VAP, Atherotech, AL). One in three patients had ≥25 percentile units discordance between TC/HDL-C and LDL-C while one in four had ≥25 percentile units discordance between TC/HDL-C and non-HDL-C. The proportion of patients with TC/HDL-C > LDL-C by ≥25 percentile units increased from 3% at triglycerides non-HDL-C discordance by ≥25 percentile units increased from 6% to 21%. In those with 86% of the variance in percentile discordance between TC/HDL-C vs. LDL-C and non-HDL-C. Conclusions —In this contemporary, cross-sectional, big data analysis of U.S. adults who underwent advanced lipid testing, the extent of patient-level discordance suggests that TC/HDL-C may offer potential additional information to LDL-C and non-HDL-C. Future studies are required to determine the clinical implications of this observation. Clinical Trial Registration Information —www.clinicaltrials.gov. Identifier: [NCT01698489][1]. [1]: /lookup/external-ref?link_type=CLINTRIALGOV&access_num=NCT01698489&atom=%2Fcirculationaha%2Fearly%2F2015%2F07%2F02%2FCIRCULATIONAHA.115.016163.atom
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Very Large Database of Lipids: Rationale and Design
Clinical cardiology, 2013Co-Authors: Seth S. Martin, Michael J. Blaha, Peter P. Toth, Parag H. Joshi, John W. Mcevoy, Haitham M. Ahmed, Mohamed B. Elshazly, Kristopher J. Swiger, Erin D. Michos, Peter O. KwiterovichAbstract:Blood lipids have major cardiovascular and public health implications. Lipid-lowering drugs are prescribed based in part on categorization of patients into normal or abnormal lipid metabolism, yet relatively little emphasis has been placed on: (1) the accuracy of current lipid measures used in clinical practice, (2) the reliability of current categorizations of dyslipidemia states, and (3) the relationship of advanced lipid characterization to other cardiovascular disease biomarkers. To these ends, we developed the Very Large Database of Lipids (NCT01698489), an ongoing Database protocol that harnesses deidentified data from the daily operations of a commercial lipid laboratory. The Database includes individuals who were referred for clinical purposes for a Vertical Auto Profile (Atherotech Inc., Birmingham, AL), which directly measures cholesterol concentrations of low-density lipoprotein, very low-density lipoprotein, intermediate-density lipoprotein, high-density lipoprotein, their subclasses, and lipoprotein(a). Individual Very Large Database of Lipids studies, ranging from studies of measurement accuracy, to dyslipidemia categorization, to biomarker associations, to characterization of rare lipid disorders, are investigator-initiated and utilize peer-reviewed statistical analysis plans to address a priori hypotheses/aims. In the first Database harvest (Very Large Database of Lipids 1.0) from 2009 to 2011, there were 1 340 614 adult and 10 294 pediatric patients; the adult sample had a median age of 59 years (interquartile range, 49–70 years) with even representation by sex. Lipid distributions closely matched those from the population-representative National Health and Nutrition Examination Survey. The second harvest of the Database (Very Large Database of Lipids 2.0) is underway. Overall, the Very Large Database of Lipids Database provides an opportunity for collaboration and new knowledge generation through careful examination of granular lipid data on a Large scale.
Jermainechristopher - One of the best experts on this subject based on the ideXlab platform.
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Online Random Shuffling of Large Database Tables
IEEE Transactions on Knowledge and Data Engineering, 2007Co-Authors: JermainechristopherAbstract:Many applications require a randomized ordering of input data. Examples include algorithms for online aggregation, data mining, and various randomized algorithms. Most existing work seems to assume...
Ambuj K Singh - One of the best experts on this subject based on the ideXlab platform.
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efficient and robust detection of duplicate videos in a Large Database
IEEE Transactions on Circuits and Systems for Video Technology, 2010Co-Authors: Anindya Sarkar, Vishwakarma Singh, Pradiptya Ghosh, B S Manjunath, Ambuj K SinghAbstract:We present an efficient and accurate method for duplicate video detection in a Large Database using video fingerprints. We have empirically chosen the color layout descriptor, a compact and robust frame-based descriptor, to create fingerprints which are further encoded by vector quantization (VQ). We propose a new nonmetric distance measure to find the similarity between the query and a Database video fingerprint and experimentally show its superior performance over other distance measures for accurate duplicate detection. Efficient search cannot be performed for high-dimensional data using a nonmetric distance measure with existing indexing techniques. Therefore, we develop novel search algorithms based on precomputed distances and new dataset pruning techniques yielding practical retrieval times. We perform experiments with a Database of 38 000 videos, worth 1600 h of content. For individual queries with an average duration of 60 s (about 50% of the average Database video length), the duplicate video is retrieved in 0.032 s, on Intel Xeon with CPU 2.33 GHz, with a very high accuracy of 97.5%.
