Intelligent Data Analysis for Biomedical Applications

Intelligent Data Analysis for Biomedical Applications
Author: Hemanth D. Jude,Deepak Gupta,Valentina Emilia Balas
Publsiher: Academic Press
Total Pages: 294
Release: 2019-03-15
Genre: Computers
ISBN: 9780128156438

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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

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
Publsiher: Academic Press
Total Pages: 310
Release: 2019-11-29
Genre: Technology & Engineering
ISBN: 9780128144831

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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

Advances in Intelligent Data Analysis and Applications

Advances in Intelligent Data Analysis and Applications
Author: Jeng-Shyang Pan,Valentina Emilia Balas,Chien-Ming Chen
Publsiher: Springer Nature
Total Pages: 383
Release: 2021-11-25
Genre: Technology & Engineering
ISBN: 9789811650369

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This book constitutes the Proceeding of the Sixth International Conference on Intelligent Data Analysis and Applications, October 15–18, 2019, Arad, Romania. This edition is technically co-sponsored by “Aurel Vlaicu” University of Arad, Romania, Southwest Jiaotong University, Fujian University of Technology, Chang’an University, Shandong University of Science and Technology, Fujian Provincial Key Lab of Big Data Mining and Applications, and National Demonstration Center for Experimental Electronic Information and Electrical Technology Education (Fujian University of Technology), China, Romanian Academy, and General Association of Engineers in Romania - Arad Section. The book covers a range of topics: Machine Learning, Intelligent Control, Pattern Recognition, Computational Intelligence, Signal Analysis, Modeling and Visualization, Multimedia Sensing and Sensory Systems, Signal control, Imaging and Processing, Information System Security, Cryptography and Cryptanalysis, Databases and Data Mining, Information Hiding, Cloud Computing, Information Retrieval and Integration, Robotics, Control, Agents, Command, Control, Communication and Computers (C4), Swarming Technology, Sensor Technology, Smart cities. The book offers a timely, board snapshot of new development including trends and challenges that are yielding recent research directions in different areas of intelligent data analysis and applications. The book provides useful information to professors, researchers, and graduated students in area of intelligent data analysis and applications.

Intelligent Data Analysis and Applications

Intelligent Data Analysis and Applications
Author: Ajith Abraham,Xin Hua Jiang,Václav Snášel,Jeng-Shyang Pan
Publsiher: Springer
Total Pages: 560
Release: 2015-07-14
Genre: Technology & Engineering
ISBN: 9783319212067

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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.
Publsiher: IGI Global
Total Pages: 598
Release: 2009-04-30
Genre: Computers
ISBN: 9781605663159

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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.

Computational Intelligence and Data Sciences

Computational Intelligence and Data Sciences
Author: Taylor & Francis Group
Publsiher: CRC Press
Total Pages: 272
Release: 2022-02-23
Genre: Electronic Book
ISBN: 1032123133

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This book presents futuristic trends in computational intelligence including algorithms used in different application domains in health informatics covering bio-medical, bioinformatics, &biological sciences. It provides conceptual framework with a focus on computational intelligence techniques in biomedical engineering &health informatics.

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
Publsiher: Academic Press
Total Pages: 292
Release: 2020-10-18
Genre: Science
ISBN: 9780128193150

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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

Computational Intelligence and Predictive Analysis for Medical Science

Computational Intelligence and Predictive Analysis for Medical Science
Author: Poonam Tanwar,Praveen Kumar,Seema Rawat,Masoud Mohammadian,Saif Ahmad
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 333
Release: 2021-11-08
Genre: Computers
ISBN: 9783110715347

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This book uncovers stakes and possibilities offered by Computational Intelligence and Predictive Analytics to Medical Science. The main focus is on data technologies,classification, analysis and mining, information retrieval, and in the algorithms needed to elaborate the informations. A section with use cases and applications follows the two main parts of the book, respectively dedicated to the foundations and techniques of the discipline.

Bioinformatics and Medical Applications

Bioinformatics and Medical Applications
Author: A. Suresh,S. Vimal,Y. Harold Robinson,Dhinesh Kumar Ramaswami,R. Udendhran
Publsiher: John Wiley & Sons
Total Pages: 352
Release: 2022-03-24
Genre: Computers
ISBN: 9781119792659

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BIOINFORMATICS AND MEDICAL APPLICATIONS The main topics addressed in this book are big data analytics problems in bioinformatics research such as microarray data analysis, sequence analysis, genomics-based analytics, disease network analysis, techniques for big data analytics, and health information technology. Bioinformatics and Medical Applications: Big Data Using Deep Learning Algorithms analyses massive biological datasets using computational approaches and the latest cutting-edge technologies to capture and interpret biological data. The book delivers various bioinformatics computational methods used to identify diseases at an early stage by assembling cutting-edge resources into a single collection designed to enlighten the reader on topics focusing on computer science, mathematics, and biology. In modern biology and medicine, bioinformatics is critical for data management. This book explains the bioinformatician’s important tools and examines how they are used to evaluate biological data and advance disease knowledge. The editors have curated a distinguished group of perceptive and concise chapters that presents the current state of medical treatments and systems and offers emerging solutions for a more personalized approach to healthcare. Applying deep learning techniques for data-driven solutions in health information allows automated analysis whose method can be more advantageous in supporting the problems arising from medical and health-related information. Audience The primary audience for the book includes specialists, researchers, postgraduates, designers, experts, and engineers, who are occupied with biometric research and security-related issues.

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics

Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics
Author: Sunil Kumar Dhal,Srinivas Prasad,Sudhir Kumar Mohapatra,Subhendu Kumar Pani
Publsiher: John Wiley & Sons
Total Pages: 352
Release: 2022-05-20
Genre: Computers
ISBN: 9781119792352

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BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

Translational Bioinformatics in Healthcare and Medicine

Translational Bioinformatics in Healthcare and Medicine
Author: Anonim
Publsiher: Academic Press
Total Pages: 254
Release: 2021-05-13
Genre: Business & Economics
ISBN: 9780323898904

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Translational Bioinformatics in Healthcare and Medicine offers an overview of main principles of bioinformatics, biological databases, clinical informatics, health informatics, viroinformatics and real-case applications of translational bioinformatics in healthcare. Written by experts from both technology and clinical sides, the content brings together essential knowledge to make the best of recent advancements of the field. The book discusses topics such as next generation sequence analysis, genomics in clinical care, IoT applications, blockchain technology, patient centered interoperability of EHR, health data mining, and translational bioinformatics methods for drug discovery and drug repurposing. In addition, it discusses the role of bioinformatics in cancer research and viroinformatics approaches to counter viral diseases through informatics. This is a valuable resource for bioinformaticians, clinicians, healthcare professionals, graduate students and several members of biomedical field who are interested in learning more about how bioinformatics can impact in their research and practice. Covers recent advancements in translational bioinformatics and its healthcare applications Discusses integrative and multidisciplinary approaches to U-healthcare systems development and management Bridges the gap among various knowledge domains in the field, integrating both technological and clinical knowledge into practical content

Intelligent Techniques for Data Analysis in Diverse Settings

Intelligent Techniques for Data Analysis in Diverse Settings
Author: Celebi, Numan
Publsiher: IGI Global
Total Pages: 353
Release: 2016-04-20
Genre: Computers
ISBN: 9781522500766

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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.

Intelligent Data Analysis

Intelligent Data Analysis
Author: Deepak Gupta,Siddhartha Bhattacharyya,Ashish Khanna,Kalpna Sagar
Publsiher: John Wiley & Sons
Total Pages: 400
Release: 2020-07-07
Genre: Technology & Engineering
ISBN: 9781119544456

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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 with data analysis tools.

Deep Learning Techniques for Biomedical and Health Informatics

Deep Learning Techniques for Biomedical and Health Informatics
Author: Basant Agarwal,Valentina Emilia Balas,Lakhmi C. Jain,Ramesh Chandra Poonia,Manisha Sharma
Publsiher: Academic Press
Total Pages: 367
Release: 2020-01-14
Genre: Science
ISBN: 9780128190623

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Deep Learning Techniques for Biomedical and Health Informatics provides readers with the state-of-the-art in deep learning-based methods for biomedical and health informatics. The book covers not only the best-performing methods, it also presents implementation methods. The book includes all the prerequisite methodologies in each chapter so that new researchers and practitioners will find it very useful. Chapters go from basic methodology to advanced methods, including detailed descriptions of proposed approaches and comprehensive critical discussions on experimental results and how they are applied to Biomedical Engineering, Electronic Health Records, and medical image processing. Examines a wide range of Deep Learning applications for Biomedical Engineering and Health Informatics, including Deep Learning for drug discovery, clinical decision support systems, disease diagnosis, prediction and monitoring Discusses Deep Learning applied to Electronic Health Records (EHR), including health data structures and management, deep patient similarity learning, natural language processing, and how to improve clinical decision-making Provides detailed coverage of Deep Learning for medical image processing, including optimizing medical big data, brain image analysis, brain tumor segmentation in MRI imaging, and the future of biomedical image analysis

Artificial Intelligence for Data Driven Medical Diagnosis

Artificial Intelligence for Data Driven Medical Diagnosis
Author: Deepak Gupta,Utku Kose,Bao Le Nguyen,Siddhartha Bhattacharyya
Publsiher: Walter de Gruyter GmbH & Co KG
Total Pages: 326
Release: 2021-02-08
Genre: Computers
ISBN: 9783110668322

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This book collects research works of data-driven medical diagnosis done via Artificial Intelligence based solutions, such as Machine Learning, Deep Learning and Intelligent Optimization. Physical devices powered with Artificial Intelligence are gaining importance in diagnosis and healthcare. Medical data from different sources can also be analyzed via Artificial Intelligence techniques for more effective results.