Intelligent Data Analysis for Biomedical Applications

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  • Author : Hemanth D. Jude
  • Publisher : Academic Press
  • Pages : 294 pages
  • ISBN : 0128156430
  • Rating : /5 from reviews
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Download or Read online Intelligent Data Analysis for Biomedical Applications full in PDF, ePub and kindle. this book written by Hemanth D. Jude and published by Academic Press which was released on 15 March 2019 with total page 294 pages. We cannot guarantee that Intelligent Data Analysis for Biomedical Applications book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers, scientists, engineers and practitioners interested in intelligent data analysis, knowledge discovery, and decision support in databases. Provides the methods and tools necessary for intelligent data analysis and gives solutions to problems resulting from automated data collection Contains an analysis of medical databases to provide diagnostic expert systems Addresses the integration of intelligent data analysis techniques within biomedical information systems

Intelligent Data Analysis for Biomedical Applications

Intelligent Data Analysis for Biomedical Applications
  • Author : Hemanth D. Jude,Deepak Gupta,Valentina Emilia Balas
  • Publisher : Academic Press
  • Release : 15 March 2019
GET THIS BOOK Intelligent Data Analysis for Biomedical Applications

Intelligent Data Analysis for Biomedical Applications: Challenges and Solutions presents specialized statistical, pattern recognition, machine learning, data abstraction and visualization tools for the analysis of data and discovery of mechanisms that create data. It provides computational methods and tools for intelligent data analysis, with an emphasis on problem-solving relating to automated data collection, such as computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and more. This book provides useful references for educational institutions, industry professionals, researchers,

Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications
  • Author : Khalid Al-Jabery,Tayo Obafemi-Ajayi,Gayla Olbricht,Donald Wunsch
  • Publisher : Academic Press
  • Release : 29 November 2019
GET THIS BOOK Computational Learning Approaches to Data Analytics in Biomedical Applications

Computational Learning Approaches to Data Analytics in Biomedical Applications provides a unified framework for biomedical data analysis using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms and techniques, and connections between statistical analysis and clustering. The book introduces and discusses the major problems relating to data analytics, provides a review of influential and state-of-the-art learning algorithms for biomedical applications, reviews cluster validity indices and how to select the appropriate index, and includes

Intelligent Data Analysis

Intelligent Data Analysis
  • Author : Deepak Gupta,Siddhartha Bhattacharyya,Ashish Khanna,Kalpna Sagar
  • Publisher : John Wiley & Sons
  • Release : 27 April 2020
GET THIS BOOK Intelligent Data Analysis

This book focuses on methods and tools for intelligent data analysis, aimed at narrowing the increasing gap between data gathering and data comprehension, and emphasis will also be given to solving of problems which result from automated data collection, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring, and so on. This book aims to describe the different approaches of Intelligent Data Analysis from a practical point of view: solving common life problems

Deep Learning for Data Analytics

Deep Learning for Data Analytics
  • Author : Himansu Das,Chittaranjan Pradhan,Nilanjan Dey
  • Publisher : Academic Press
  • Release : 29 May 2020
GET THIS BOOK Deep Learning for Data Analytics

Deep learning, a branch of Artificial Intelligence and machine learning, has led to new approaches to solving problems in a variety of domains including data science, data analytics and biomedical engineering. Deep Learning for Data Analytics: Foundations, Biomedical Applications and Challenges provides readers with a focused approach for the design and implementation of deep learning concepts using data analytics techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers of nonlinear

Hybrid Computational Intelligence

Hybrid Computational Intelligence
  • Author : Siddhartha Bhattacharyya,Vaclav Snasel,Deepak Gupta,Ashish Khanna
  • Publisher : Academic Press
  • Release : 05 March 2020
GET THIS BOOK Hybrid Computational Intelligence

Hybrid Computational Intelligence: Challenges and Utilities is a comprehensive resource that begins with the basics and main components of computational intelligence. It brings together many different aspects of the current research on HCI technologies, such as neural networks, support vector machines, fuzzy logic and evolutionary computation, while also covering a wide range of applications and implementation issues, from pattern recognition and system modeling, to intelligent control problems and biomedical applications. The book also explores the most widely used applications of

Data Analytics in Biomedical Engineering and Healthcare

Data Analytics in Biomedical Engineering and Healthcare
  • Author : Kun Chang Lee,Sanjiban Sekhar Roy,Pijush Samui,Vijay Kumar
  • Publisher : Academic Press
  • Release : 23 October 2020
GET THIS BOOK Data Analytics in Biomedical Engineering and Healthcare

Data Analytics in Biomedical Engineering and Healthcare explores key applications using data analytics, machine learning, and deep learning in health sciences and biomedical data. The book is useful for those working with big data analytics in biomedical research, medical industries, and medical research scientists. The book covers health analytics, data science, and machine and deep learning applications for biomedical data, covering areas such as predictive health analysis, electronic health records, medical image analysis, computational drug discovery, and genome structure prediction

Intelligent Data Analysis in Medicine and Pharmacology

Intelligent Data Analysis in Medicine and Pharmacology
  • Author : Nada Lavrač,E. T. Keravnou,Blaz Zupan
  • Publisher : Springer
  • Release : 30 September 1997
GET THIS BOOK Intelligent Data Analysis in Medicine and Pharmacology

Intelligent data analysis, data mining and knowledge discovery in databases have recently gained the attention of a large number of researchers and practitioners. This is witnessed by the rapidly increasing number of submissions and participants at related conferences and workshops, by the emergence of new journals in this area (e.g., Data Mining and Knowledge Discovery, Intelligent Data Analysis, etc.), and by the increasing number of new applications in this field. In our view, the awareness of these challenging research

Applications of Big Data in Healthcare

Applications of Big Data in Healthcare
  • Author : Ashish Khanna,Deepak Gupta,Nilanjan Dey
  • Publisher : Academic Press
  • Release : 10 March 2021
GET THIS BOOK Applications of Big Data in Healthcare

Applications of Big Data in Healthcare: Theory and Practice begins with the basics of Big Data analysis and introduces the tools, processes and procedures associated with Big Data analytics. The book unites healthcare with Big Data analysis and uses the advantages of the latter to solve the problems faced by the former. The authors present the challenges faced by the healthcare industry, including capturing, storing, searching, sharing and analyzing data. This book illustrates the challenges in the applications of Big

Deep Learning for Biomedical Data Analysis

Deep Learning for Biomedical Data Analysis
  • Author : Mourad Elloumi
  • Publisher : Springer
  • Release : 09 May 2021
GET THIS BOOK Deep Learning for Biomedical Data Analysis

This book is the first overview on Deep Learning (DL) and biomedical data analysis. It surveys the most recent techniques and approaches in this field, with both a broad coverage and enough depth to be of practical use to working professionals. This book offers enough fundamental and technical information on these techniques, approaches and the related problems without overcrowding the reader's head. It presents the results of the latest investigations in the field of DL for biomedical data analysis. The

Internet of Things in Biomedical Engineering

Internet of Things in Biomedical Engineering
  • Author : Valentina E. Balas,Le Hoang Son,Sudan Jha,Manju Khari,Raghvendra Kumar
  • Publisher : Academic Press
  • Release : 14 June 2019
GET THIS BOOK Internet of Things in Biomedical Engineering

Internet of Things in Biomedical Engineering presents the most current research in Internet of Things (IoT) applications for clinical patient monitoring and treatment. The book takes a systems-level approach for both human-factors and the technical aspects of networking, databases and privacy. Sections delve into the latest advances and cutting-edge technologies, starting with an overview of the Internet of Things and biomedical engineering, as well as a focus on ‘daily life.’ Contributors from various experts then discuss ‘computer assisted anthropology,’ CLOUDFALL,

Telemedicine Technologies

Telemedicine Technologies
  • Author : Hemanth D. Jude,Valentina Emilia Balas
  • Publisher : Academic Press
  • Release : 04 May 2019
GET THIS BOOK Telemedicine Technologies

Telemedicine Technologies: Big Data, Deep Learning, Robotics, Mobile and Remote Applications for Global Healthcare illustrates the innovative concepts, methodologies and frameworks that will increase the feasibility of the existing telemedicine system. The book also focuses on showcasing prototypes of remote healthcare systems, thus emphasizing the data processing side that is often recognized as the backbone of any telemedicine system. Illustrates the innovative concepts, methodologies and frameworks that will increase the feasibility of the existing telemedicine system Focuses on showcasing prototypes

Biomedical Applications Based on Natural and Artificial Computing

Biomedical Applications Based on Natural and Artificial Computing
  • Author : José Manuel Ferrández Vicente,José Ramón Álvarez-Sánchez,Félix de la Paz López,Javier Toledo Moreo,Hojjat Adeli
  • Publisher : Springer
  • Release : 27 May 2017
GET THIS BOOK Biomedical Applications Based on Natural and Artificial Computing

The two volumes LNCS 10337 and 10338 constitute the proceedings of the International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2017, held in Corunna, Spain, in June 2017. The total of 102 full papers was carefully reviewed and selected from 194 submissions during two rounds of reviewing and improvement. The papers are organized in two volumes, one on natural and artificial computation for biomedicine and neuroscience, addressing topics such as theoretical neural computation; models; natural computing in bioinformatics; physiological computing in affective smart

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare
  • Author : Janmenjoy Nayak,Bighnaraj Naik,Danilo Pelusi,Asit Kumar Das
  • Publisher : Academic Press
  • Release : 08 April 2021
GET THIS BOOK Handbook of Computational Intelligence in Biomedical Engineering and Healthcare

Handbook of Computational Intelligence in Biomedical Engineering and Healthcare helps readers analyze and conduct advanced research in specialty healthcare applications surrounding oncology, genomics and genetic data, ontologies construction, bio-memetic systems, biomedical electronics, protein structure prediction, and biomedical data analysis. The book provides the reader with a comprehensive guide to advanced computational intelligence, spanning deep learning, fuzzy logic, connectionist systems, evolutionary computation, cellular automata, self-organizing systems, soft computing, and hybrid intelligent systems in biomedical and healthcare applications. Sections focus on important