Biomedical Literature Mining

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Biomedical Text Mining

Kalpana Raja
Biomedical Text Mining Book PDF

Author : Kalpana Raja
Publisher : Springer Nature
Page : 324 pages
File Size : 42,8 Mb
Release : 2022-06-17
Category : Science
ISBN : 9781071623053

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Biomedical Text Mining by Kalpana Raja Pdf

This volume details step-by-step instructions on biomedical literature mining protocols. Chapters guide readers through various topics such as, disease comorbidity, literature-based discovery, protocols to combine literature mining, machine learning for predicting biomedical discoveries, and uncovering unknown public knowledge by combining two pieces of information from different sets of PubMed articles. Additional chapters discuss the importance of data science to understand outbreaks such as COVID-19. Written in the format of the highly successful Methods in Molecular Biology series, each chapter includes an introduction to the topic, lists necessary materials and reagents, includes tips on troubleshooting and known pitfalls, and step-by-step, readily reproducible protocols. Authoritative and cutting-edge, Biomedical Text Mining aims to be a useful practical guide to researches to help further their studies.

Biomedical Literature Mining

Vinod D. Kumar,Hannah Jane Tipney
Biomedical Literature Mining Book PDF

Author : Vinod D. Kumar,Hannah Jane Tipney
Publisher : Humana
Page : 0 pages
File Size : 42,9 Mb
Release : 2016-09-24
Category : Science
ISBN : 1493954296

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Biomedical Literature Mining by Vinod D. Kumar,Hannah Jane Tipney Pdf

Biomedical Literature Mining, discusses the multiple facets of modern biomedical literature mining and its many applications in genomics and systems biology. The volume is divided into three sections focusing on information retrieval, integrated text-mining approaches and domain-specific mining methods. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Biomedical Literature Mining is designed as a useful bioinformatics resource in biomedical literature text mining for both those long experienced in or entirely new to, the field.

Mining the Biomedical Literature

Hagit Shatkay,Mark Craven
Mining the Biomedical Literature Book PDF

Author : Hagit Shatkay,Mark Craven
Publisher : MIT Press
Page : 151 pages
File Size : 49,9 Mb
Release : 2012
Category : Computers
ISBN : 9780262017695

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Mining the Biomedical Literature by Hagit Shatkay,Mark Craven Pdf

The authors offer an accessible introduction to key ideas in biomedical text mining. The chapters cover such topics as the sources of biomedical text; text-analysis methods in natural language processing; the tasks of information extraction, information retrieval, and text categorization; and methods for empirically assessing textmining systems.

Biomedical Literature Mining

Vinod D. Kumar,Hannah Jane Tipney
Biomedical Literature Mining Book PDF

Author : Vinod D. Kumar,Hannah Jane Tipney
Publisher : Humana Press
Page : 288 pages
File Size : 55,8 Mb
Release : 2014-04-30
Category : Science
ISBN : 1493907107

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Biomedical Literature Mining by Vinod D. Kumar,Hannah Jane Tipney Pdf

Biomedical Literature Mining, discusses the multiple facets of modern biomedical literature mining and its many applications in genomics and systems biology. The volume is divided into three sections focusing on information retrieval, integrated text-mining approaches and domain-specific mining methods. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible laboratory protocols and key tips on troubleshooting and avoiding known pitfalls. Authoritative and practical, Biomedical Literature Mining is designed as a useful bioinformatics resource in biomedical literature text mining for both those long experienced in or entirely new to, the field.

Text Mining of Web-Based Medical Content

Amy Neustein
Text Mining of Web Based Medical Content Book PDF

Author : Amy Neustein
Publisher : Walter de Gruyter GmbH & Co KG
Page : 327 pages
File Size : 40,7 Mb
Release : 2014-10-09
Category : Computers
ISBN : 9781614519768

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Text Mining of Web-Based Medical Content by Amy Neustein Pdf

• Includes Text Mining and Natural Language Processing Methods for extracting information from electronic health records and biomedical literature. • Analyzes text analytic tools for new media such as online forums, social media posts, tweets and video sharing. • Demonstrates how to use speech and audio technologies for improving access to online content for the visually impaired. Text Mining of Web-Based Medical Content examines various approaches to deriving high quality information from online biomedical literature, electronic health records, query search terms, social media posts and tweets. Using some of the latest empirical methods of knowledge extraction, the authors show how online content, generated by both professionals and laypersons, can be mined for valuable information about disease processes, adverse drug reactions not captured during clinical trials, and tropical fever outbreaks. Additionally, the authors show how to perform infromation extraction on a hospital intranet, how to build a social media search engine to glean information about patients' own experiences interacting with healthcare professionals, and how to improve access to online health information. This volume provides a wealth of timely material for health informatic professionals and machine learning, data mining, and natural language researchers. Topics in this book include: • Mining Biomedical Literature and Clinical Narratives • Medication Information Extraction • Machine Learning Techniques for Mining Medical Search Queries • Detecting the Level of Personal Health Information Revealed in Social Media • Curating Layperson’s Personal Experiences with Health Care from Social Media and Twitter • Health Dialogue Systems for Improving Access to Online Content • Crowd-based Audio Clips to Improve Online Video Access for the Visually Impaired • Semantic-based Visual Information Retrieval for Mining Radiographic Image Data • Evaluating the Importance of Medical Terminology in YouTube Video Titles and Descriptions

Biomedical Natural Language Processing

Kevin Bretonnel Cohen,Dina Demner-Fushman
Biomedical Natural Language Processing Book PDF

Author : Kevin Bretonnel Cohen,Dina Demner-Fushman
Publisher : John Benjamins Publishing Company
Page : 174 pages
File Size : 43,9 Mb
Release : 2014-02-15
Category : Computers
ISBN : 9789027271068

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Biomedical Natural Language Processing by Kevin Bretonnel Cohen,Dina Demner-Fushman Pdf

Biomedical Natural Language Processing is a comprehensive tour through the classic and current work in the field. It discusses all subjects from both a rule-based and a machine learning approach, and also describes each subject from the perspective of both biological science and clinical medicine. The intended audience is readers who already have a background in natural language processing, but a clear introduction makes it accessible to readers from the fields of bioinformatics and computational biology, as well. The book is suitable as a reference, as well as a text for advanced courses in biomedical natural language processing and text mining.

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 : 49,8 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

Text Mining for Biology and Biomedicine

Sophia Ananiadou
Text Mining for Biology and Biomedicine Book PDF

Author : Sophia Ananiadou
Publisher : Artech House Publishers
Page : 312 pages
File Size : 44,7 Mb
Release : 2006
Category : Computers
ISBN : UOM:39015063312048

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Text Mining for Biology and Biomedicine by Sophia Ananiadou Pdf

Here's the first focused book that puts the full range of cutting-edge biological text mining techniques and tools at your command. This comprehensive volume describes the methods of natural language processing (NLP) and their applications in the biological domain, and spells out in detail the various lexical, terminological, and ontological resources now at your disposal - and how best to utilize them.

Clinical Text Mining

Hercules Dalianis
Clinical Text Mining Book PDF

Author : Hercules Dalianis
Publisher : Springer
Page : 192 pages
File Size : 43,9 Mb
Release : 2018-05-14
Category : Computers
ISBN : 9783319785035

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Clinical Text Mining by Hercules Dalianis Pdf

This open access book describes the results of natural language processing and machine learning methods applied to clinical text from electronic patient records. It is divided into twelve chapters. Chapters 1-4 discuss the history and background of the original paper-based patient records, their purpose, and how they are written and structured. These initial chapters do not require any technical or medical background knowledge. The remaining eight chapters are more technical in nature and describe various medical classifications and terminologies such as ICD diagnosis codes, SNOMED CT, MeSH, UMLS, and ATC. Chapters 5-10 cover basic tools for natural language processing and information retrieval, and how to apply them to clinical text. The difference between rule-based and machine learning-based methods, as well as between supervised and unsupervised machine learning methods, are also explained. Next, ethical concerns regarding the use of sensitive patient records for research purposes are discussed, including methods for de-identifying electronic patient records and safely storing patient records. The book’s closing chapters present a number of applications in clinical text mining and summarise the lessons learned from the previous chapters. The book provides a comprehensive overview of technical issues arising in clinical text mining, and offers a valuable guide for advanced students in health informatics, computational linguistics, and information retrieval, and for researchers entering these fields.

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 : 40,8 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.

Artificial Intelligence

Marco Antonio Aceves-Fernandez
Artificial Intelligence Book PDF

Author : Marco Antonio Aceves-Fernandez
Publisher : BoD – Books on Demand
Page : 466 pages
File Size : 48,7 Mb
Release : 2018-06-27
Category : Computers
ISBN : 9781789233643

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Artificial Intelligence by Marco Antonio Aceves-Fernandez Pdf

Artificial intelligence (AI) is taking an increasingly important role in our society. From cars, smartphones, airplanes, consumer applications, and even medical equipment, the impact of AI is changing the world around us. The ability of machines to demonstrate advanced cognitive skills in taking decisions, learn and perceive the environment, predict certain behavior, and process written or spoken languages, among other skills, makes this discipline of paramount importance in today's world. Although AI is changing the world for the better in many applications, it also comes with its challenges. This book encompasses many applications as well as new techniques, challenges, and opportunities in this fascinating area.

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 : 40,9 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.

New Opportunities for Sentiment Analysis and Information Processing

Sharaff, Aakanksha,Sinha, G. R.,Bhatia, Surbhi
New Opportunities for Sentiment Analysis and Information Processing Book PDF

Author : Sharaff, Aakanksha,Sinha, G. R.,Bhatia, Surbhi
Publisher : IGI Global
Page : 311 pages
File Size : 40,9 Mb
Release : 2021-06-25
Category : Computers
ISBN : 9781799880639

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New Opportunities for Sentiment Analysis and Information Processing by Sharaff, Aakanksha,Sinha, G. R.,Bhatia, Surbhi Pdf

Multinational organizations have begun to realize that sentiment mining plays an important role for decision making and market strategy. The revolutionary growth of digital marketing not only changes the market game, but also brings forth new opportunities for skilled professionals and expertise. Currently, the technologies are rapidly changing, and artificial intelligence (AI) and machine learning are contributing as game-changing technologies. These are not only trending but are also increasingly popular among data scientists and data analysts. New Opportunities for Sentiment Analysis and Information Processing provides interdisciplinary research in information retrieval and sentiment analysis including studies on extracting sentiments from textual data, sentiment visualization-based dimensionality reduction for multiple features, and deep learning-based multi-domain sentiment extraction. The book also optimizes techniques used for sentiment identification and examines applications of sentiment analysis and emotion detection. Covering such topics as communication networks, natural language processing, and semantic analysis, this book is essential for data scientists, data analysts, IT specialists, scientists, researchers, academicians, and students.

Mining Text Data

Charu C. Aggarwal,ChengXiang Zhai
Mining Text Data Book PDF

Author : Charu C. Aggarwal,ChengXiang Zhai
Publisher : Springer Science & Business Media
Page : 527 pages
File Size : 46,9 Mb
Release : 2012-02-03
Category : Computers
ISBN : 9781461432234

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Mining Text Data by Charu C. Aggarwal,ChengXiang Zhai Pdf

Text mining applications have experienced tremendous advances because of web 2.0 and social networking applications. Recent advances in hardware and software technology have lead to a number of unique scenarios where text mining algorithms are learned. Mining Text Data introduces an important niche in the text analytics field, and is an edited volume contributed by leading international researchers and practitioners focused on social networks & data mining. This book contains a wide swath in topics across social networks & data mining. Each chapter contains a comprehensive survey including the key research content on the topic, and the future directions of research in the field. There is a special focus on Text Embedded with Heterogeneous and Multimedia Data which makes the mining process much more challenging. A number of methods have been designed such as transfer learning and cross-lingual mining for such cases. Mining Text Data simplifies the content, so that advanced-level students, practitioners and researchers in computer science can benefit from this book. Academic and corporate libraries, as well as ACM, IEEE, and Management Science focused on information security, electronic commerce, databases, data mining, machine learning, and statistics are the primary buyers for this reference book.

Graph Neural Networks: Foundations, Frontiers, and Applications

Lingfei Wu,Peng Cui,Jian Pei,Liang Zhao
Graph Neural Networks Foundations Frontiers and Applications Book PDF

Author : Lingfei Wu,Peng Cui,Jian Pei,Liang Zhao
Publisher : Springer Nature
Page : 701 pages
File Size : 45,7 Mb
Release : 2022-01-03
Category : Computers
ISBN : 9789811660542

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Graph Neural Networks: Foundations, Frontiers, and Applications by Lingfei Wu,Peng Cui,Jian Pei,Liang Zhao Pdf

Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning. This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.