Titlebook: Machine Learning in Healthcare Informatics; Sumeet Dua,U. Rajendra Acharya,Prerna Dua Book 2014 Springer-Verlag Berlin Heidelberg 2014 Alg

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Introduction to Machine Learning in Healthcare Informatics, reduce healthcare costs and the movement towards personalized healthcare, the healthcare industry faces changes in three core areas namely, electronic record management, data integration, and computer aided diagnoses. Machine learning a complex field in itself offers a wide range of tools, techniqu

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Wavelet-based Machine Learning Techniques for ECG Signal Analysis,nges in its amplitude and duration are not well manifested in time and frequency domains. Therefore, in this chapter, we introduce a machine-learning approach to screen arrhythmia from normal sinus rhythm from the ECG. The methodology consists of R-point detection using the Pan-Tompkins algorithm, d

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Pixel-based Machine Learning in Computer-Aided Diagnosis of Lung and Colon Cancer,e in CAD, because representing lesions and organs requires a complex model that has a number of parameters to determine; thus, medical pattern recognition essentially requires “l(fā)earning from examples” to determine the parameters of the model. Machine learning has been used to classify lesions into c

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Rule Learning in Healthcare and Health Services Research, deal with background knowledge, efficiency, and exportability. Rule learning is known to satisfy the above criteria. This chapter introduces rule learning in healthcare, presents very expressive attributional rules, briefly describes the AQ21 rule learning system, and discusses three application ar

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