Biomedical Data Mining For Information Retrieval

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Biomedical Data Mining for Information Retrieval

Sujata Dash,Subhendu Kumar Pani,S. Balamurugan,Ajith Abraham
Biomedical Data Mining for Information Retrieval Book PDF

Author : Sujata Dash,Subhendu Kumar Pani,S. Balamurugan,Ajith Abraham
Publisher : John Wiley & Sons
Page : 450 pages
File Size : 53,9 Mb
Release : 2021-08-24
Category : Computers
ISBN : 9781119711247

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Biomedical Data Mining for Information Retrieval by Sujata Dash,Subhendu Kumar Pani,S. Balamurugan,Ajith Abraham Pdf

BIOMEDICAL DATA MINING FOR INFORMATION RETRIEVAL This book not only emphasizes traditional computational techniques, but discusses data mining, biomedical image processing, information retrieval with broad coverage of basic scientific applications. Biomedical Data Mining for Information Retrieval comprehensively covers the topic of mining biomedical text, images and visual features towards information retrieval. Biomedical and health informatics is an emerging field of research at the intersection of information science, computer science, and healthcare and brings tremendous opportunities and challenges due to easily available and abundant biomedical data for further analysis. The aim of healthcare informatics is to ensure the high-quality, efficient healthcare, better treatment and quality of life by analyzing biomedical and healthcare data including patient’s data, electronic health records (EHRs) and lifestyle. Previously, it was a common requirement to have a domain expert to develop a model for biomedical or healthcare; however, recent advancements in representation learning algorithms allows us to automatically to develop the model. Biomedical image mining, a novel research area, due to the vast amount of available biomedical images, increasingly generates and stores digitally. These images are mainly in the form of computed tomography (CT), X-ray, nuclear medicine imaging (PET, SPECT), magnetic resonance imaging (MRI) and ultrasound. Patients’ biomedical images can be digitized using data mining techniques and may help in answering several important and critical questions relating to healthcare. Image mining in medicine can help to uncover new relationships between data and reveal new useful information that can be helpful for doctors in treating their patients. Audience Researchers in various fields including computer science, medical informatics, healthcare IOT, artificial intelligence, machine learning, image processing, clinical big data analytics.

Interactive Knowledge Discovery and Data Mining in Biomedical Informatics

Andreas Holzinger,Igor Jurisica
Interactive Knowledge Discovery and Data Mining in Biomedical Informatics Book PDF

Author : Andreas Holzinger,Igor Jurisica
Publisher : Springer
Page : 357 pages
File Size : 54,8 Mb
Release : 2014-06-17
Category : Computers
ISBN : 9783662439685

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Interactive Knowledge Discovery and Data Mining in Biomedical Informatics by Andreas Holzinger,Igor Jurisica Pdf

One of the grand challenges in our digital world are the large, complex and often weakly structured data sets, and massive amounts of unstructured information. This “big data” challenge is most evident in biomedical informatics: the trend towards precision medicine has resulted in an explosion in the amount of generated biomedical data sets. Despite the fact that human experts are very good at pattern recognition in dimensions of = 3; most of the data is high-dimensional, which makes manual analysis often impossible and neither the medical doctor nor the biomedical researcher can memorize all these facts. A synergistic combination of methodologies and approaches of two fields offer ideal conditions towards unraveling these problems: Human–Computer Interaction (HCI) and Knowledge Discovery/Data Mining (KDD), with the goal of supporting human capabilities with machine learning./ppThis state-of-the-art survey is an output of the HCI-KDD expert network and features 19 carefully selected and reviewed papers related to seven hot and promising research areas: Area 1: Data Integration, Data Pre-processing and Data Mapping; Area 2: Data Mining Algorithms; Area 3: Graph-based Data Mining; Area 4: Entropy-Based Data Mining; Area 5: Topological Data Mining; Area 6 Data Visualization and Area 7: Privacy, Data Protection, Safety and Security.

Information Retrieval

William Hersh
Information Retrieval Book PDF

Author : William Hersh
Publisher : Springer Science & Business Media
Page : 524 pages
File Size : 42,9 Mb
Release : 2006-05-04
Category : Medical
ISBN : 9780387226781

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Information Retrieval by William Hersh Pdf

Coupled with the growth of the World Wide Web, the topic of health information retrieval has had a tremendous impact on consumer health information. With the aid of newly added questions and discussions at the end of each chapter, this Second Edition covers theory practical applications, evaluation, and research directions of all aspects of medical information retireval systems.

Predictive Modeling in Biomedical Data Mining and Analysis

Sudipta Roy,Lalit Mohan Goyal,Valentina Emilia Balas,Basant Agarwal,Mamta Mittal
Predictive Modeling in Biomedical Data Mining and Analysis Book PDF

Author : Sudipta Roy,Lalit Mohan Goyal,Valentina Emilia Balas,Basant Agarwal,Mamta Mittal
Publisher : Academic Press
Page : 346 pages
File Size : 52,9 Mb
Release : 2022-08-28
Category : Science
ISBN : 9780323914451

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Predictive Modeling in Biomedical Data Mining and Analysis by Sudipta Roy,Lalit Mohan Goyal,Valentina Emilia Balas,Basant Agarwal,Mamta Mittal Pdf

Predictive Modeling in Biomedical Data Mining and Analysis presents major technical advancements and research findings in the field of machine learning in biomedical image and data analysis. The book examines recent technologies and studies in preclinical and clinical practice in computational intelligence. The authors present leading-edge research in the science of processing, analyzing and utilizing all aspects of advanced computational machine learning in biomedical image and data analysis. As the application of machine learning is spreading to a variety of biomedical problems, including automatic image segmentation, image classification, disease classification, fundamental biological processes, and treatments, this is an ideal reference. Machine Learning techniques are used as predictive models for many types of applications, including biomedical applications. These techniques have shown impressive results across a variety of domains in biomedical engineering research. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood, hence the need for new resources and information. Includes predictive modeling algorithms for both Supervised Learning and Unsupervised Learning for medical diagnosis, data summarization and pattern identification Offers complete coverage of predictive modeling in biomedical applications, including data visualization, information retrieval, data mining, image pre-processing and segmentation, mathematical models and deep neural networks Provides readers with leading-edge coverage of biomedical data processing, including high dimension data, data reduction, clinical decision-making, deep machine learning in large data sets, multimodal, multi-task, and transfer learning, as well as machine learning with Internet of Biomedical Things applications

Data Mining for Biomedical Applications

Jinyan Li,Qiang Yang,Ah-Hwee Tan
Data Mining for Biomedical Applications Book PDF

Author : Jinyan Li,Qiang Yang,Ah-Hwee Tan
Publisher : Springer Science & Business Media
Page : 163 pages
File Size : 50,7 Mb
Release : 2006-03-23
Category : Computers
ISBN : 9783540331049

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Data Mining for Biomedical Applications by Jinyan Li,Qiang Yang,Ah-Hwee Tan Pdf

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

Medical Informatics

Hsinchun Chen,Sherrilynne S. Fuller,Carol Friedman,William Hersh
Medical Informatics Book PDF

Author : Hsinchun Chen,Sherrilynne S. Fuller,Carol Friedman,William Hersh
Publisher : Springer Science & Business Media
Page : 656 pages
File Size : 52,5 Mb
Release : 2006-07-19
Category : Medical
ISBN : 9780387257396

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Medical Informatics by Hsinchun Chen,Sherrilynne S. Fuller,Carol Friedman,William Hersh Pdf

Comprehensively presents the foundations and leading application research in medical informatics/biomedicine. The concepts and techniques are illustrated with detailed case studies. Authors are widely recognized professors and researchers in Schools of Medicine and Information Systems from the University of Arizona, University of Washington, Columbia University, and Oregon Health & Science University. Related Springer title, Shortliffe: Medical Informatics, has sold over 8000 copies The title will be positioned at the upper division and graduate level Medical Informatics course and a reference work for practitioners in the field.

Data Mining in Bioinformatics

Jason T. L. Wang
Data Mining in Bioinformatics Book PDF

Author : Jason T. L. Wang
Publisher : Springer Science & Business Media
Page : 356 pages
File Size : 40,9 Mb
Release : 2005
Category : Computers
ISBN : 1852336714

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Data Mining in Bioinformatics by Jason T. L. Wang Pdf

Written especially for computer scientists, all necessary biology is explained. Presents new techniques on gene expression data mining, gene mapping for disease detection, and phylogenetic knowledge discovery.

Data Mining for Biomarker Discovery

Panos M. Pardalos,Petros Xanthopoulos,Michalis Zervakis
Data Mining for Biomarker Discovery Book PDF

Author : Panos M. Pardalos,Petros Xanthopoulos,Michalis Zervakis
Publisher : Springer Science & Business Media
Page : 246 pages
File Size : 48,6 Mb
Release : 2012-02-11
Category : Business & Economics
ISBN : 9781461421078

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Data Mining for Biomarker Discovery by Panos M. Pardalos,Petros Xanthopoulos,Michalis Zervakis Pdf

Biomarker discovery is an important area of biomedical research that may lead to significant breakthroughs in disease analysis and targeted therapy. Biomarkers are biological entities whose alterations are measurable and are characteristic of a particular biological condition. Discovering, managing, and interpreting knowledge of new biomarkers are challenging and attractive problems in the emerging field of biomedical informatics. This volume is a collection of state-of-the-art research into the application of data mining to the discovery and analysis of new biomarkers. Presenting new results, models and algorithms, the included contributions focus on biomarker data integration, information retrieval methods, and statistical machine learning techniques. This volume is intended for students, and researchers in bioinformatics, proteomics, and genomics, as well engineers and applied scientists interested in the interdisciplinary application of data mining techniques.

Biological Data Mining

Jake Y. Chen,Stefano Lonardi
Biological Data Mining Book PDF

Author : Jake Y. Chen,Stefano Lonardi
Publisher : Chapman and Hall/CRC
Page : 0 pages
File Size : 51,5 Mb
Release : 2009-09-01
Category : Computers
ISBN : 1420086847

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Biological Data Mining by Jake Y. Chen,Stefano Lonardi Pdf

Like a data-guzzling turbo engine, advanced data mining has been powering post-genome biological studies for two decades. Reflecting this growth, Biological Data Mining presents comprehensive data mining concepts, theories, and applications in current biological and medical research. Each chapter is written by a distinguished team of interdisciplinary data mining researchers who cover state-of-the-art biological topics. The first section of the book discusses challenges and opportunities in analyzing and mining biological sequences and structures to gain insight into molecular functions. The second section addresses emerging computational challenges in interpreting high-throughput Omics data. The book then describes the relationships between data mining and related areas of computing, including knowledge representation, information retrieval, and data integration for structured and unstructured biological data. The last part explores emerging data mining opportunities for biomedical applications. This volume examines the concepts, problems, progress, and trends in developing and applying new data mining techniques to the rapidly growing field of genome biology. By studying the concepts and case studies presented, readers will gain significant insight and develop practical solutions for similar biological data mining projects in the future.

Data Mining in Medical and Biological Research

Eugenia Giannopoulou
Data Mining in Medical and Biological Research Book PDF

Author : Eugenia Giannopoulou
Publisher : BoD – Books on Demand
Page : 334 pages
File Size : 40,5 Mb
Release : 2008-11-01
Category : Medical
ISBN : 9789537619305

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Data Mining in Medical and Biological Research by Eugenia Giannopoulou Pdf

This book intends to bring together the most recent advances and applications of data mining research in the promising areas of medicine and biology from around the world. It consists of seventeen chapters, twelve related to medical research and five focused on the biological domain, which describe interesting applications, motivating progress and worthwhile results. We hope that the readers will benefit from this book and consider it as an excellent way to keep pace with the vast and diverse advances of new research efforts.

Data Mining in Biomedical Imaging, Signaling, and Systems

Sumeet Dua,Rajendra Acharya U
Data Mining in Biomedical Imaging Signaling and Systems Book PDF

Author : Sumeet Dua,Rajendra Acharya U
Publisher : CRC Press
Page : 434 pages
File Size : 52,9 Mb
Release : 2016-04-19
Category : Computers
ISBN : 9781439839393

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Data Mining in Biomedical Imaging, Signaling, and Systems by Sumeet Dua,Rajendra Acharya U Pdf

Data mining can help pinpoint hidden information in medical data and accurately differentiate pathological from normal data. It can help to extract hidden features from patient groups and disease states and can aid in automated decision making. Data Mining in Biomedical Imaging, Signaling, and Systems provides an in-depth examination of the biomedi

Deep Learning for Biomedical Data Analysis

Mourad Elloumi
Deep Learning for Biomedical Data Analysis Book PDF

Author : Mourad Elloumi
Publisher : Springer Nature
Page : 358 pages
File Size : 48,9 Mb
Release : 2021-07-13
Category : Medical
ISBN : 9783030716769

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Deep Learning for Biomedical Data Analysis by Mourad Elloumi Pdf

This book is the first overview on Deep Learning (DL) for 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 techniques and approaches presented in this book deal with the most important and/or the newest topics encountered in this field. They combine fundamental theory of Artificial Intelligence (AI), Machine Learning (ML) and DL with practical applications in Biology and Medicine. Certainly, the list of topics covered in this book is not exhaustive but these topics will shed light on the implications of the presented techniques and approaches on other topics in biomedical data analysis. The book finds a balance between theoretical and practical coverage of a wide range of issues in the field of biomedical data analysis, thanks to DL. The few published books on DL for biomedical data analysis either focus on specific topics or lack technical depth. The chapters presented in this book were selected for quality and relevance. The book also presents experiments that provide qualitative and quantitative overviews in the field of biomedical data analysis. The reader will require some familiarity with AI, ML and DL and will learn about techniques and approaches that deal with the most important and/or the newest topics encountered in the field of DL for biomedical data analysis. He/she will discover both the fundamentals behind DL techniques and approaches, and their applications on biomedical data. This book can also serve as a reference book for graduate courses in Bioinformatics, AI, ML and DL. The book aims not only at professional researchers and practitioners but also graduate students, senior undergraduate students and young researchers. This book will certainly show the way to new techniques and approaches to make new discoveries.

Data Mining for Biomedical Applications

Jinyan Li,Qiang Yang,Ah-Hwee Tan
Data Mining for Biomedical Applications Book PDF

Author : Jinyan Li,Qiang Yang,Ah-Hwee Tan
Publisher : Springer
Page : 0 pages
File Size : 44,9 Mb
Release : 2006-02-28
Category : Computers
ISBN : 3540331050

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Data Mining for Biomedical Applications by Jinyan Li,Qiang Yang,Ah-Hwee Tan Pdf

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

Transactions on Large-Scale Data- and Knowledge-Centered Systems IV

Christian Böhm,Johann Eder,Claudia Plant
Transactions on Large Scale Data and Knowledge Centered Systems IV Book PDF

Author : Christian Böhm,Johann Eder,Claudia Plant
Publisher : Springer
Page : 218 pages
File Size : 40,5 Mb
Release : 2011-09-25
Category : Computers
ISBN : 9783642237409

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Transactions on Large-Scale Data- and Knowledge-Centered Systems IV by Christian Böhm,Johann Eder,Claudia Plant Pdf

The LNCS journal Transactions on Large-Scale Data- and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability. Current decentralized systems still focus on data and knowledge as their main resource. Feasibility of these systems relies basically on P2P (peer-to-peer) techniques and the support of agent systems with scaling and decentralized control. Synergy between Grids, P2P systems, and agent technologies is the key to data- and knowledge-centered systems in large-scale environments. This special issue of Transactions on Large-Scale Data- and Knowledge-Centered Systems highlights some of the major challenges emerging from the biomedical applications that are currently inspiring and promoting database research. These include the management, organization, and integration of massive amounts of heterogeneous data; the semantic gap between high-level research questions and low-level data; and privacy and efficiency. The contributions cover a large variety of biological and medical applications, including genome-wide association studies, epidemic research, and neuroscience.

Computational Intelligence and Blockchain in Biomedical and Health Informatics

Pankaj Bhambri,Sita Rani,Muhammad Fahim
Computational Intelligence and Blockchain in Biomedical and Health Informatics Book PDF

Author : Pankaj Bhambri,Sita Rani,Muhammad Fahim
Publisher : CRC Press
Page : 361 pages
File Size : 51,5 Mb
Release : 2024-06-19
Category : Computers
ISBN : 9781040044094

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Computational Intelligence and Blockchain in Biomedical and Health Informatics by Pankaj Bhambri,Sita Rani,Muhammad Fahim Pdf

Advancements in computational intelligence, which encompasses artificial intelligence, machine learning, and data analytics, have revolutionized the way we process and analyze biomedical and health data. These techniques offer novel approaches to understanding complex biological systems, improving disease diagnosis, optimizing treatment plans, and enhancing patient outcomes. Computational Intelligence and Blockchain in Biomedical and Health Informatics introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields and provides a framework and summary of the various methods. The book emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. Techniques to analyze the impacts on the biomedical and health Informatics domains are discussed along with major challenges in deployment. Rounding out the book are highlights of the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability along with two case studies. This book is highly beneficial to educators, researchers, and anyone involved with health data. Features: • Introduces the role of computational intelligence and blockchain in the biomedical and health informatics fields. • Provides a framework and a summary of various computational intelligence and blockchain methods. • Emphasizes the role of advanced computational techniques and offers demonstrative examples throughout. • Techniques to analyze the impact on biomedical and health informatics are discussed along with major challenges in deployment. • Highlights the transformative potential of computational intelligence and blockchain in addressing critical issues in healthcare from disease diagnosis and personalized medicine to health data management and interoperability.