microsoft excel for mac data analysis tools

beginning excel what if data analysis tools phần 1 pps

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Advanced Methods and Tools for ECG Data Analysis - Part 1 ppt

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... ShashiAugust 24, 2006 11:32 Chan-Horizon Azuaje˙BookAdvanced Methods and Tools for ECG Data Analysis Gari D. CliffordFrancisco AzuajePatrick E. McSharryEditorsartechhouse.com P1: ShashiAugust ... Cataloging-in-Publication Data A catalog record for this book is available from this U.S. Library of Congress.British Library Cataloguing in Publication Data A catalogue record for this book is available ... together with methods for applying these models to ECG analysis. Chapter 5 describes a unified framework for linear filtering techniques includingwavelets, principal component analysis, neural networks,...

Advanced Methods and Tools for ECG Data Analysis - Part 2 doc

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... sufficient for the signalprocessing tasks.11. Data formats: When storing data, it is important to use an accurate andverifiable data format (at each step). If data are to be converted to anotherformat, ... to ask when choosing a data format and access libraries include:ãWhat are the data going to be used for? ãAre the data format and libraries extensible?ãIs the data format compact?ãAre the ... plug-ins.Therefore, it is easily extensible for any new data formats, programming languages,viewing tools, or signal processing libraries. A set of signal processing plugins areavailable for this...

Advanced Methods and Tools for ECG Data Analysis - Part 3 docx

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... (sensitivity, specificity) on the MIT-BIH database [2]of 93.2%, 94.4% for sinus rhythm, 100%, 96.2% for superventricular tachycardia,97.7%, 98.6% for VT, and 98.6%, 97.7% for VFIB. They also report classificationstatistics ... segmentare used). Utilization of the LSP, therefore, reveals a theoretical lower informationthreshold for accepting segments of an RR tachogram for spectral analysis in theupper HF region. If RR intervals ... nonlinear nature of the ECG. Techniques for nonlinear analysis are therefore presented in Chapter 6. However, before reading the chapteron nonlinear analysis, it is advisable to read the following...

Advanced Methods and Tools for ECG Data Analysis - Part 4 ppsx

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... technique for performing JTFA andbelongs to a family of JTFA techniques that include the STFT, the Wigner Villetransform (WVT), the Zhao-Atlas-Marks distribution, and the Hilbert transform.2Unfortunately, ... correspond to the noise.In general, transforms can be categorized as orthogonal or biorthogonal trans-formations. For orthogonal transformations, the transformed signal is the same135 P1: ShashiAugust ... nomenclature. For each filter, twowavelets are shown; one for signal decomposition (on the left side) and one for signal reconstruc-tion (on the right side). Type waveinfo (‘bior’ ) in Matlab for more...

Advanced Methods and Tools for ECG Data Analysis - Part 5 pdf

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... Applications, Oxford, U.K.: OxfordUniversity Press, 1998.[27] MacKay, D. J. C., “Maximum Likelihood and Covariant Algorithms for IndependentComponent Analysis, ” http://www.inference.phy.cam.ac.uk/mackay/abstracts/ica.html,1996, ... network.inputs and outputs; the target data vector is simply the input data vector. There-fore, no labeling of training data is required. An auto-associative neural networkperforms dimensionality reduction ... orthogonalwavelets (except for the Haar wavelet). Therefore, bi or 3.3 is a good choice for ageneral ECG filter. It should be noted that the filtering performance of each waveletwill be different for different...

Advanced Methods and Tools for ECG Data Analysis - Part 6 docx

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... for reimbursement, and the suggestion by the U.S. Centers for Medicare and MedicaidServices (CMS) for the inclusion of TWA analysis in the proposed national registry for SCA management [10].7.2 Phenomenology ... andit therefore has a bandpass filtering effect leading to a lossy transformation of the data into a set of integrable Gaussians distributed over time. This approach couldtherefore be used ... applications, ranging from 250 to1,000 Hz, is also sufficient for TWA analysis. Some time-domain analyses for TWAfound essentially identical results for sampling frequencies of 250 to 1,000 Hz,with only...

Advanced Methods and Tools for ECG Data Analysis - Part 7 ppt

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... which are visually informative and accessible for analysis at any time instant.Therefore, a technique which converts such point event series into a form suitable for standard analysis techniques ... Database: Standard for Evaluating Systems for the Analysis of ST-T Changes in Ambulatory Electrocardiography,” European Heart Journal,Vol. 13, 1992, pp. 1164–1172.[25] Jager, F., et al., Analysis ... not found, the procedure searches forwards in eachECG lead for up to TJ= 68 ms for a part of the waveform which “starts to flatten”(i.e., a part of waveform where slope became smaller than...

Advanced Methods and Tools for ECG Data Analysis - Part 8 docx

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... waveform in the data set. Therefore, we chose to distribute thewaveforms at random among the different experts (such that each waveform wasmeasured by one expert only). For each ECG waveform, ... ECG waveform, and hence a greater degree of robustness in thewaveform segmentations.11.5 Data CollectionIn order to develop an automated system for ECG interval analysis, we collecteda data ... which perfor-mance remains acceptable;2. Bootstrap estimation of performance distributions, to determine if perfor-mance is critically dependent on the choice of the database used for testing;3....

Advanced Methods and Tools for ECG Data Analysis - Part 9 ppsx

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... interval analysis, however, we can automatically highlight thosewaveforms which are least suitable to analysis by machine (and thus most in needof analysis by a human expert). This strategy therefore ... interval analysis systems are unable to differentiate be-tween normal ECG waveforms (for which the automated annotations are generallyreliable) and abnormal or unusual ECG waveforms (for which ... different clinical classes. This is, for example, observed in ECGwaveforms contained in the MIT-BIH Arrhythmia Database [9]. In this databasethere are ECG waveforms of 12 types of abnormal beats:...

Advanced Methods and Tools for ECG Data Analysis - Part 10 pps

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... support data analysis tasks and applications [64]. A relevant solutionconsists of applying eXtensible Markup Language (XML) for representing ECGinformation. ecgML [65], a markup language for ECG data ... by XML for supporting data exchange between different ECG data acquisition and analysis devices. Suchrepresentation approaches may facilitate data mining using heterogeneous softwareplatforms. ... “SOM-Based Data Visualization Methods,” Intelligent Data Analysis, Vol. 3,No. 2, 1999, pp. 111–126.[22] Ultsch, A., and H. P. Siemon, “Kohonen’s Self Organizing Feature Maps for Exploratory Data Analysis, ”...

Statistical Methods for Survival Data Analysis - Third Edition potx

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... diabetes mellitus (NIDDM) were examined in32EXAMPLES OF SURVIVAL DATA ANALYSIS PrefaceStatistical methods for survival data analysis have continued to ﬂourish in thelast two decades. Applications ... edition of Statisti-cal Methods for Survival Data Analysis is intended to provide a comprehensiveintroduction of the most commonly used methods for analyzing survival data. It begins with basic deﬁnitions ... Instead, wehave included discussions of more statistical methods for survival data analysis. A brief summary of the improvements made for the third edition is givenbelow.1. Two additional distributions,...

Báo cáo khoa hoc:" EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis" docx

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... the analysis of repeated measurements, Biometrics44 (1988) 959–971.[4] Diggle P.J., Liang K.Y., Zeger S.L., Analysis of longitudinal data, OxfordScience Publications, Clarendon Press, Oxford, ... covariance structure (10 parameters).ML EM-REML for longitudinal data 139POW). However, since the value of −2Lm for model 4 is slightly higher thanthat for model 3, it is the EM procedure which ... models for longitudinal data analysis. 132 J L. Foulley et al.3. EM IMPLEMENTATIONLet γ =(g, r)be the 3+K(K +1)/2 parameter vector and x =(y, β, u)be the complete data vector...

Báo cáo sinh học: "Speeding up the Consensus Clustering methodology for microarray data analysis" doc

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... the o nes for CNS R at, NCI60, PBM and Yeast datasets since theones for Leukemia and Lymphoma are comparable tothose obtained for CNS Rat and NCI60 and thereforeare redundant. As for the Benchmark ... Genclust: AGenetic Algorithm for Clustering Gene Expression Data. BMCBioinformatics 2005, 6:289.35. Krzanowski W, Lai Y: A Criterion for Determining the Number of Groupsin a Dataset Using Sum of Squares ... R: Algorithms for Clustering Data Englewood Cliffs: Prentice-Hall; 1988.14. Seal S, Comarina S, Aluru S: An Optimal Hierarchical Clustering Algorithm For Gene Expression Data. Information Processing...