Titlebook: Classification in BioApps; Automation of Decisi Nilanjan Dey,Amira S. Ashour,Surekha Borra Book 2018 Springer International Publishing AG 2

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ECG Signal Dimensionality Reduction-Based Atrial Fibrillation Detectiond conjugate symmetric-complex Hadamard transform (CS-CHT) to eliminate redundancy. In DWT, the features extracted contain both time and frequency components. In CHT and CS–CHT, the features of an ECG signal can be obtained only by considering four orders: natural, Paley or dyadic, sequency and Cal–S

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A Bio-application for Accident Victim Identification Using Biometricsises the input data, but also minimizes the dimensionality of the data. An ELM is applied to a preprocessed image to extract the unique features for victim identification. An effective optimal cost region matcher (OCRM) with deep learning techniques is applied to enhance the accuracy of victim recog

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Researching Cultures of Learningn objective assessment (OA), rather than subjective assessment (SA). Three types of OA-based IQA algorithms are presented in detail: full reference-based IQA (FR-IQA) algorithms; no reference-based IQA (NR-IQA) algorithms and reduced reference-based IQA (RR-IQA) algorithms.

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https://doi.org/10.1057/9781137296344efficient system for the classification of mocardial infarction (MI) using an artificial neural network (ANN) (Levenberg-Marquardt Neural Network) and two different classifiers. Our experimental results show that an FFPSO algorithm with an ANN give a 99.3% rate of accuracy when combining the MIT-BIH and the NSR databases.

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Ruth McAlister,Fabian Campbell-Westr implementation. These advancements in bioinformatics, along with developments in machine learning-based classification, would provide powerful toolboxes for the classification of transcriptome information available through RNA-Seq data.

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