January 16, 2021

Download Ebook Free Intelligent Data Analysis For Biomedical Applications

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 Date : 2019-03-15
Category : Computers
Total pages :294
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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

Deep Learning for Data Analytics

Deep Learning for Data Analytics
Author : Himansu Das,Chittaranjan Pradhan,Nilanjan Dey
Publisher : Academic Press
Release Date : 2020-05-29
Category : Science
Total pages :218
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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 processing, which aids in feature extraction and learning in supervised and unsupervised ways, including classification and pattern analysis. Deep learning transforms data through a cascade of layers, helping systems analyze and process complex data sets. Deep learning algorithms extract high level complex data and process these complex sets to relatively simpler ideas formulated in the preceding level of the hierarchy. The authors of this book focus on suitable data analytics methods to solve complex real world problems such as medical image recognition, biomedical engineering, and object tracking using deep learning methodologies. The book provides a pragmatic direction for researchers who wish to analyze large volumes of data for business, engineering, and biomedical applications. Deep learning architectures including deep neural networks, recurrent neural networks, and deep belief networks can be used to help resolve problems in applications such as natural language processing, speech recognition, computer vision, bioinoformatics, audio recognition, drug design, and medical image analysis. Presents the latest advances in Deep Learning for data analytics and biomedical engineering applications. Discusses Deep Learning techniques as they are being applied in the real world of biomedical engineering and data science, including Deep Learning networks, deep feature learning, deep learning toolboxes, performance evaluation, Deep Learning optimization, deep auto-encoders, and deep neural networks Provides readers with an introduction to Deep Learning, along with coverage of deep belief networks, convolutional neural networks, Restricted Boltzmann Machines, data analytics basics, enterprise data science, predictive analysis, optimization for Deep Learning, and feature selection using Deep Learning

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 Date : 2019-11-29
Category : Technology & Engineering
Total pages :310
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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 an overview of statistical methods that can be applied to increase confidence in the clustering framework and analysis of the results obtained. Includes an overview of data analytics in biomedical applications and current challenges Updates on the latest research in supervised learning algorithms and applications, clustering algorithms and cluster validation indices Provides complete coverage of computational and statistical analysis tools for biomedical data analysis Presents hands-on training on the use of Python libraries, MATLAB® tools, WEKA, SAP-HANA and R/Bioconductor

Intelligent Data Analysis and Applications

Intelligent Data Analysis and Applications
Author : Ajith Abraham,Xin Hua Jiang,Václav Snášel,Jeng-Shyang Pan
Publisher : Springer
Release Date : 2015-07-14
Category : Computers
Total pages :560
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This volume of Advances in Intelligent Systems and Computing contains accepted papers presented in the main track of ECC 2015, the Second Euro-China Conference on Intelligent Data Analysis and Applications. The aim of ECC is to provide an internationally respected forum for scientific research in the broad area of intelligent data analysis, computational intelligence, signal processing, and all associated applications of AIs. The second edition of ECC was organized jointly by VSB - Technical University of Ostrava, Czech Republic, and Fujian University of Technology, Fuzhou, China. The conference, organized under the patronage of Mr. Miroslav Novak, President of the Moravian-Silesian Region, took place in late June and early July 2015 in the Campus of the VSB - Technical University of Ostrava, Czech Republic.

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications

Handbook of Research on Advanced Techniques in Diagnostic Imaging and Biomedical Applications
Author : Exarchos, Themis P.,Papadopoulos, Athanasios,Fotiadis, Dimitrios I.
Publisher : IGI Global
Release Date : 2009-04-30
Category : Computers
Total pages :598
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"This book includes state-of-the-art methodologies that introduce biomedical imaging in decision support systems and their applications in clinical practice"--Provided by publisher.

Intelligent Techniques for Data Analysis in Diverse Settings

Intelligent Techniques for Data Analysis in Diverse Settings
Author : Celebi, Numan
Publisher : IGI Global
Release Date : 2016-04-20
Category : Computers
Total pages :353
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Data analysis forms the basis of many forms of research ranging from the scientific to the governmental. With the advent of machine intelligence and neural networks, extracting, modeling, and approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other. Intelligent Techniques for Data Analysis in Diverse Settings addresses the specialized requirements of data analysis in a comprehensive way. This title contains a comprehensive overview of the most innovative recent approaches borne from intelligent techniques such as neural networks, rough sets, fuzzy sets, and metaheuristics. Combining new data analysis technologies, applications, emerging trends, and case studies, this publication reviews the intelligent, technological, and organizational aspects of the field. This book is ideally designed for IT professionals and students, data analysis specialists, healthcare providers, and policy makers.

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 Date : 2020-10-23
Category : Science
Total pages :292
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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 using predictive modeling. Case studies demonstrate big data applications in healthcare using the MapReduce and Hadoop frameworks. Examines the development and application of data analytics applications in biomedical data Presents innovative classification and regression models for predicting various diseases Discusses genome structure prediction using predictive modeling Shows readers how to develop clinical decision support systems Shows researchers and specialists how to use hybrid learning for better medical diagnosis, including case studies of healthcare applications using the MapReduce and Hadoop frameworks

Hybrid Computational Intelligence

Hybrid Computational Intelligence
Author : Siddhartha Bhattacharyya,Vaclav Snasel,Deepak Gupta,Ashish Khanna
Publisher : Academic Press
Release Date : 2020-03-05
Category : Computers
Total pages :250
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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 hybrid computation as well as the history of their development. Each individual methodology provides hybrid systems with complementary reasoning and searching methods which allow the use of domain knowledge and empirical data to solve complex problems. Provides insights into the latest research trends in hybrid intelligent algorithms and architectures Focuses on the application of hybrid intelligent techniques for pattern mining and recognition, in big data analytics, and in human-computer interaction Features hybrid intelligent applications in biomedical engineering and healthcare informatics

Advances in Intelligent Data Analysis VI

Advances in Intelligent Data Analysis VI
Author : A. Fazel Famili,Joost N. Kok,José M. Pena,Ad Feelders,Arno Siebes
Publisher : Springer Science & Business Media
Release Date : 2005-08-30
Category : Business & Economics
Total pages :522
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This book constitutes the refereed proceedings of the 6th International Conference on Intelligent Data Analysis, IDA 2005, held in Madrid, Spain in September 2005. The 46 revised papers presented together with two tutorials and two invited talks were carefully reviewed and selected from 184 submissions. All current aspects of this interdisciplinary field are addressed; the areas covered include statistics, machine learning, data mining, classification and pattern recognition, clustering, applications, modeling, and interactive dynamic data visualization.

Advances in Intelligent Analysis of Medical Data and Decision Support Systems

Advances in Intelligent Analysis of Medical Data and Decision Support Systems
Author : Roumen Kountchev,Barna Iantovics
Publisher : Springer
Release Date : 2013-02-11
Category : Computers
Total pages :247
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This volume is a result of the fruitful and vivid discussions during the MedDecSup'2012 International Workshop bringing together a relevant body of knowledge, and new developments in the increasingly important field of medical informatics. This carefully edited book presents new ideas aimed at the development of intelligent processing of various kinds of medical information and the perfection of the contemporary computer systems for medical decision support. The book presents advances of the medical information systems for intelligent archiving, processing, analysis and search-by-content which will improve the quality of the medical services for every patient and of the global healthcare system. The book combines in a synergistic way theoretical developments with the practicability of the approaches developed and presents the last developments and achievements in medical informatics to a broad range of readers: engineers, mathematicians, physicians, and PhD students.

Data Mining and Medical Knowledge Management: Cases and Applications

Data Mining and Medical Knowledge Management: Cases and Applications
Author : Berka, Petr,Rauch, Jan,Zighed, Djamel Abdelkader
Publisher : IGI Global
Release Date : 2009-02-28
Category : Computers
Total pages :464
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The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.

Artificial Intelligence in Medicine

Artificial Intelligence in Medicine
Author : Riccardo Bellazzi,Ameen Abu-Hanna,Jim Hunter
Publisher : Springer Science & Business Media
Release Date : 2007-06-29
Category : Medical
Total pages :509
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This book constitutes the refereed proceedings of the 11th Conference on Artificial Intelligence in Medicine in Europe, AIME 2007, held in Amsterdam, The Netherlands in July 2007. The 28 revised full papers and 38 revised short papers presented were carefully reviewed and selected from 137 submissions. The papers are organized in topical sections on agent-based systems, temporal data mining, machine learning and knowledge discovery, text mining, natural language processing and generation, ontologies, decision support systems, applications of AI-based image processing techniques, protocols and guidelines, as well as workflow systems.

Big Data Analytics for Intelligent Healthcare Management

Big Data Analytics for Intelligent Healthcare Management
Author : Nilanjan Dey,Himansu Das,Bighnaraj Naik,H S Behera
Publisher : Academic Press
Release Date : 2019-04-15
Category : Science
Total pages :312
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Big Data Analytics for Intelligent Healthcare Management covers both the theory and application of hardware platforms and architectures, the development of software methods, techniques and tools, applications and governance, and adoption strategies for the use of big data in healthcare and clinical research. The book provides the latest research findings on the use of big data analytics with statistical and machine learning techniques that analyze huge amounts of real-time healthcare data. Examines the methodology and requirements for development of big data architecture, big data modeling, big data as a service, big data analytics, and more Discusses big data applications for intelligent healthcare management, such as revenue management and pricing, predictive analytics/forecasting, big data integration for medical data, algorithms and techniques, etc. Covers the development of big data tools, such as data, web and text mining, data mining, optimization, machine learning, cloud in big data with Hadoop, big data in IoT, and more

Intelligent Data Security Solutions for e-Health Applications

Intelligent Data Security Solutions for e-Health Applications
Author : Amit Kumar Singh,Mohamed Elhoseny
Publisher : Academic Press
Release Date : 2020-09-02
Category : Computers
Total pages :340
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E-health applications such as tele-medicine, tele-radiology, tele-ophthalmology, and tele-diagnosis are very promising and have immense potential to improve global healthcare. They can improve access, equity, and quality through the connection of healthcare facilities and healthcare professionals, diminishing geographical and physical barriers. One critical issue, however, is related to the security of data transmission and access to the technologies of medical information. Currently, medical-related identity theft costs billions of dollars each year and altered medical information can put a person’s health at risk through misdiagnosis, delayed treatment or incorrect prescriptions. Yet, the use of hand-held devices for storing, accessing, and transmitting medical information is outpacing the privacy and security protections on those devices. Researchers are starting to develop some imperceptible marks to ensure the tamper-proofing, cost effective, and guaranteed originality of the medical records. However, the robustness, security and efficient image archiving and retrieval of medical data information against these cyberattacks is a challenging area for researchers in the field of e-health applications. Intelligent Data Security Solutions for e-Health Applications focuses on cutting-edge academic and industry-related research in this field, with particular emphasis on interdisciplinary approaches and novel techniques to provide security solutions for smart applications. The book provides an overview of cutting-edge security techniques and ideas to help graduate students, researchers, as well as IT professionals who want to understand the opportunities and challenges of using emerging techniques and algorithms for designing and developing more secure systems and methods for e-health applications. Investigates new security and privacy requirements related to eHealth technologies and large sets of applications Reviews how the abundance of digital information on system behavior is now being captured, processed, and used to improve and strengthen security and privacy Provides an overview of innovative security techniques which are being developed to ensure the guaranteed authenticity of transmitted, shared or stored data/information

Data Mining for Biomedical Applications

Data Mining for Biomedical Applications
Author : Jinyan Li,Qiang Yang,Ah-Hwee Tan
Publisher : Springer Science & Business Media
Release Date : 2006-03-23
Category : Computers
Total pages :155
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This book constitutes the refereed proceedings of the International Workshop on Data Mining for Biomedical Applications, BioDM 2006, held in Singapore in conjunction with the 10th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2006). The 14 revised full papers presented together with one keynote talk were carefully reviewed and selected from 35 submissions. The papers are organized in topical sections