Application Of Biomedical Text Mining
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Artificial Intelligence
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Author : Marco Antonio Aceves-Fernandez
language : en
Publisher: BoD – Books on Demand
Release Date : 2018-06-27
Artificial Intelligence written by Marco Antonio Aceves-Fernandez and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-27 with Computers categories.
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.
Text Mining Approaches For Biomedical Data
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Author : Aditi Sharan
language : en
Publisher: Springer Nature
Release Date : 2024-09-03
Text Mining Approaches For Biomedical Data written by Aditi Sharan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-03 with Computers categories.
The book 'Text Mining Approaches for Biomedical Data' delves into the fascinating realm of text mining in healthcare. It provides an in-depth understanding of how Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing healthcare research and patient care. The book covers a wide range of topics such as mining textual data in biomedical and health databases, analyzing literature and clinical trials, and demonstrating various applications of text mining in healthcare. This book is a guide for effectively representing textual data using vectors, knowledge graphs, and other advanced techniques. It covers various text mining applications, building descriptive and predictive models, and evaluating them. Additionally, it includes building machine learning models using textual data, covering statistical and deep learning approaches. This book is designed to be a valuable reference for computer science professionals, researchers in the biomedical field, and clinicians. It provides practical guidance and promotes collaboration between different disciplines. Therefore, it is a must-read for anyone who is interested in the intersection of text mining and healthcare.
Clinical Text Mining
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Author : Hercules Dalianis
language : en
Publisher: Springer
Release Date : 2018-05-14
Clinical Text Mining written by Hercules Dalianis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-14 with Computers categories.
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.
Mining The Biomedical Literature
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Author : Hagit Shatkay
language : en
Publisher: MIT Press
Release Date : 2012
Mining The Biomedical Literature written by Hagit Shatkay and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Computers categories.
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.
Application Of Biomedical Text Mining
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Author : Lejun Gong
language : en
Publisher:
Release Date : 2018
Application Of Biomedical Text Mining written by Lejun Gong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Computers categories.
With the enormous volume of biological literature, increasing growth phenomenon due to the high rate of new publications is one of the most common motivations for the biomedical text mining. Aiming at this massive literature to process, it could extract more biological information for mining biomedical knowledge. Using the information will help understand the mechanism of disease generation, promote the development of disease diagnosis technology, and promote the development of new drugs in the field of biomedical research. Based on the background, this chapter introduces the rise of biomedical text mining. Then, it describes the biomedical text-mining technology, namely natural language processing, including the several components. This chapter emphasizes the two aspects in biomedical text mining involving static biomedical information recognization and dynamic biomedical information extraction using instance analysis from our previous works. The aim is to provide a way to quickly understand biomedical text mining for some researchers.
Mining Text Data
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Author : Charu C. Aggarwal
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-03
Mining Text Data written by Charu C. Aggarwal and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-03 with Computers categories.
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.
Text Mining For Biology And Biomedicine
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Author : Sophia Ananiadou
language : en
Publisher: Artech House Publishers
Release Date : 2006
Text Mining For Biology And Biomedicine written by Sophia Ananiadou and has been published by Artech House Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computers categories.
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.
Biomedical Text Mining
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Author : Kalpana Raja
language : en
Publisher: Springer Nature
Release Date : 2022-06-17
Biomedical Text Mining written by Kalpana Raja and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-17 with Science categories.
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.
Biological Data Mining And Its Applications In Healthcare
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Author : Xiaoli Li
language : en
Publisher: World Scientific
Release Date : 2013-11-28
Biological Data Mining And Its Applications In Healthcare written by Xiaoli Li and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-28 with Science categories.
Biologists are stepping up their efforts in understanding the biological processes that underlie disease pathways in the clinical contexts. This has resulted in a flood of biological and clinical data from genomic and protein sequences, DNA microarrays, protein interactions, biomedical images, to disease pathways and electronic health records. To exploit these data for discovering new knowledge that can be translated into clinical applications, there are fundamental data analysis difficulties that have to be overcome. Practical issues such as handling noisy and incomplete data, processing compute-intensive tasks, and integrating various data sources, are new challenges faced by biologists in the post-genome era. This book will cover the fundamentals of state-of-the-art data mining techniques which have been designed to handle such challenging data analysis problems, and demonstrate with real applications how biologists and clinical scientists can employ data mining to enable them to make meaningful observations and discoveries from a wide array of heterogeneous data from molecular biology to pharmaceutical and clinical domains.
Theory And Applications For Advanced Text Mining
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Author : Shigeaki Sakurai
language : en
Publisher: BoD – Books on Demand
Release Date : 2012-11-21
Theory And Applications For Advanced Text Mining written by Shigeaki Sakurai and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-21 with Computers categories.
Due to the growth of computer technologies and web technologies, we can easily collect and store large amounts of text data. We can believe that the data include useful knowledge. Text mining techniques have been studied aggressively in order to extract the knowledge from the data since late 1990s. Even if many important techniques have been developed, the text mining research field continues to expand for the needs arising from various application fields. This book is composed of 9 chapters introducing advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language. I believe that this book will give new knowledge in the text mining field and help many readers open their new research fields.