Data and Text Processing for Health and Life Sciences

Data and Text Processing for Health and Life Sciences PDF Author: Francisco M. Couto
Publisher: Springer
ISBN: 3030138453
Category : Medical
Languages : en
Pages : 107

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Book Description
This open access book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text file formats, such as TSV, CSV, XML, and OWL, that can be open by any text editor or spreadsheet application. The first two chapters, Introduction and Resources, provide a brief introduction to the shell scripting and describe popular data resources in Health and Life Sciences. The third chapter, Data Retrieval, starts by introducing a common data processing task that involves multiple data resources. Then, this chapter explains how to automate each step of that task by introducing the required commands line tools one by one. The fourth chapter, Text Processing, shows how to filter and analyze text by using simple string matching techniques and regular expressions. The last chapter, Semantic Processing, shows how XPath queries and shell scripting is able to process complex data, such as the graphs used to specify ontologies. Besides being almost immutable for more than four decades and being available in most of our personal computers, shell scripting is relatively easy to learn by Health and Life specialists as a sequence of independent commands. Comprehending them is like conducting a new laboratory protocol by testing and understanding its procedural steps and variables, and combining their intermediate results. Thus, this book is particularly relevant to Health and Life specialists or students that want to easily learn how to process data and text, and which in return may facilitate and inspire them to acquire deeper bioinformatics skills in the future.

Data and Text Processing for Health and Life Sciences

Data and Text Processing for Health and Life Sciences PDF Author: Francisco M. Couto
Publisher: Springer
ISBN: 3030138453
Category : Medical
Languages : en
Pages : 107

Get Book Here

Book Description
This open access book is a step-by-step introduction on how shell scripting can help solve many of the data processing tasks that Health and Life specialists face everyday with minimal software dependencies. The examples presented in the book show how simple command line tools can be used and combined to retrieve data and text from web resources, to filter and mine literature, and to explore the semantics encoded in biomedical ontologies. To store data this book relies on open standard text file formats, such as TSV, CSV, XML, and OWL, that can be open by any text editor or spreadsheet application. The first two chapters, Introduction and Resources, provide a brief introduction to the shell scripting and describe popular data resources in Health and Life Sciences. The third chapter, Data Retrieval, starts by introducing a common data processing task that involves multiple data resources. Then, this chapter explains how to automate each step of that task by introducing the required commands line tools one by one. The fourth chapter, Text Processing, shows how to filter and analyze text by using simple string matching techniques and regular expressions. The last chapter, Semantic Processing, shows how XPath queries and shell scripting is able to process complex data, such as the graphs used to specify ontologies. Besides being almost immutable for more than four decades and being available in most of our personal computers, shell scripting is relatively easy to learn by Health and Life specialists as a sequence of independent commands. Comprehending them is like conducting a new laboratory protocol by testing and understanding its procedural steps and variables, and combining their intermediate results. Thus, this book is particularly relevant to Health and Life specialists or students that want to easily learn how to process data and text, and which in return may facilitate and inspire them to acquire deeper bioinformatics skills in the future.

Artificial Intelligence in Healthcare

Artificial Intelligence in Healthcare PDF Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385

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Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

Natural Language Processing in the Real World

Natural Language Processing in the Real World PDF Author: Jyotika Singh
Publisher: CRC Press
ISBN: 1000902269
Category : Computers
Languages : en
Pages : 393

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Book Description
Natural Language Processing in the Real World is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented. This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects.

Data Integration in the Life Sciences

Data Integration in the Life Sciences PDF Author: Sören Auer
Publisher: Springer
ISBN: 3030060160
Category : Computers
Languages : en
Pages : 223

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Book Description
This book constitutes revised selected papers from the 13th International Conference on Data Integration in the Life Sciences, DILS 2018, held in Hannover, Germany, in November 2018. The 5 full, 8 short, 3 poster and 4 demo papers presented in this volume were carefully reviewed and selected from 22 submissions. The papers are organized in topical sections named: big biomedical data integration and management; data exploration in the life sciences; biomedical data analytics; and big biomedical applications.

Artificial Intelligence-Based System Models in Healthcare

Artificial Intelligence-Based System Models in Healthcare PDF Author: A. Jose Anand
Publisher: John Wiley & Sons
ISBN: 1394242506
Category : Computers
Languages : en
Pages : 395

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Book Description
Artificial Intelligence-Based System Models in Healthcare provides a comprehensive and insightful guide to the transformative applications of AI in the healthcare system. This book is a groundbreaking exploration of the synergies between artificial intelligence and healthcare innovation. In an era where technological advancements are reshaping the landscape of medical practices, this book provides a comprehensive and insightful guide to the transformative applications of AI in healthcare systems. From conceptual foundations to practical implementations, the book serves as a roadmap for understanding the intricate relationships between AI-based system models and the evolution of healthcare delivery. The first section delves into the fundamental role of technology in reshaping the healthcare landscape. With a focus on daily life activities, decision support systems, vision-based management, and semantic frameworks, this section lays the groundwork for understanding the pivotal role of AI in revolutionizing traditional healthcare approaches. Each chapter offers a unique perspective, emphasizing the intricate integration of technology into healthcare ecosystems. The second section takes a deep dive into specific applications of AI, ranging from predictive analysis and machine learning to deep learning, image analysis, and biomedical text processing. With a focus on decision-making support systems, this section aims to demystify the complex world of AI algorithms in healthcare, offering valuable insights into their practical implications and potential impact on patient outcomes. The final section addresses the modernization of healthcare practices and envisions the future landscape of AI applications. From medical imaging and diagnostics to predicting ventilation needs in intensive care units, modernizing health record maintenance, natural language processing, chatbots for medical inquiries, secured health insurance management, and glimpses into the future, the book concludes by exploring the frontiers of AI-driven healthcare innovations. Audience This book is intended for researchers and postgraduate students in artificial intelligence and the biomedical and healthcare sectors. Medical administrators, policymakers and regulatory specialists will also have an interest.

Making Data Talk

Making Data Talk PDF Author: David E. Nelson (M.D.)
Publisher:
ISBN: 019538153X
Category : Health & Fitness
Languages : en
Pages : 340

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Book Description
The demand for health information continues to increase, but the ability of health professionals to provide it clearly remains variable. The aim of this book is (1) to summarize and synthesize research on the selection and presentation of data pertinent to public health, and (2) to provide practical suggestions, based on this research summary and synthesis, on how scientists and other public health practitioners can better communicate data to the public, policy makers, and the press in typical real-world situations. Because communication is complex and no one approach works for all audiences, the authors emphasize how to communicate data "better" (and in some instances, contrast this with how to communicate data "worse"), rather than attempting a cookbook approach. The book contains a wealth of case studies and other examples to illustrate major points, and actual situations whenever possible. Key principles and recommendations are summarized at the end of each chapter. This book will stimulate interest among public health practitioners, scholars, and students to more seriously consider ways they can understand and improve communication about data and other types of scientific information with the public, policy makers, and the press. Improved data communication will increase the chances that evidence-based scientific findings can play a greater role in improving the public's health.

Information Retrieval

Information Retrieval PDF Author: William Hersh
Publisher: Springer Science & Business Media
ISBN: 0387226788
Category : Medical
Languages : en
Pages : 524

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Book Description
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.

Big-Data Analytics for Cloud, IoT and Cognitive Computing

Big-Data Analytics for Cloud, IoT and Cognitive Computing PDF Author: Kai Hwang
Publisher: John Wiley & Sons
ISBN: 1119247292
Category : Computers
Languages : en
Pages : 432

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Book Description
The definitive guide to successfully integrating social, mobile, Big-Data analytics, cloud and IoT principles and technologies The main goal of this book is to spur the development of effective big-data computing operations on smart clouds that are fully supported by IoT sensing, machine learning and analytics systems. To that end, the authors draw upon their original research and proven track record in the field to describe a practical approach integrating big-data theories, cloud design principles, Internet of Things (IoT) sensing, machine learning, data analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data computing. Big data analytics and cognitive machine learning, as well as cloud architecture, IoT and cognitive systems are explored, and mobile cloud-IoT-interaction frameworks are illustrated with concrete system design examples. Part 2 is devoted to the principles of and algorithms for machine learning, data analytics and deep learning in big data applications. Part 3 concentrates on cloud programming software libraries from MapReduce to Hadoop, Spark and TensorFlow and describes business, educational, healthcare and social media applications for those tools. The first book describing a practical approach to integrating social, mobile, analytics, cloud and IoT (SMACT) principles and technologies Covers theory and computing techniques and technologies, making it suitable for use in both computer science and electrical engineering programs Offers an extremely well-informed vision of future intelligent and cognitive computing environments integrating SMACT technologies Fully illustrated throughout with examples, figures and approximately 150 problems to support and reinforce learning Features a companion website with an instructor manual and PowerPoint slides www.wiley.com/go/hwangIOT Big-Data Analytics for Cloud, IoT and Cognitive Computing satisfies the demand among university faculty and students for cutting-edge information on emerging intelligent and cognitive computing systems and technologies. Professionals working in data science, cloud computing and IoT applications will also find this book to be an extremely useful working resource.

Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis

Augmented Intelligence in Healthcare: A Pragmatic and Integrated Analysis PDF Author: Sushruta Mishra
Publisher: Springer Nature
ISBN: 9811910766
Category : Technology & Engineering
Languages : en
Pages : 503

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Book Description
The book discusses how augmented intelligence can increase the efficiency and speed of diagnosis in healthcare organizations. The concept of augmented intelligence can reflect the enhanced capabilities of human decision-making in clinical settings when augmented with computation systems and methods. It includes real-life case studies highlighting impact of augmented intelligence in health care. The book offers a guided tour of computational intelligence algorithms, architecture design, and applications of learning in healthcare challenges. It presents a variety of techniques designed to represent, enhance, and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It also presents specific applications of augmented intelligence in health care, and architectural models and frameworks-based augmented solutions.

Artificial Intelligence, Machine Learning, and Data Science Technologies

Artificial Intelligence, Machine Learning, and Data Science Technologies PDF Author: Neeraj Mohan
Publisher: CRC Press
ISBN: 1000460525
Category : Computers
Languages : en
Pages : 311

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Book Description
This book provides a comprehensive, conceptual, and detailed overview of the wide range of applications of Artificial Intelligence, Machine Learning, and Data Science and how these technologies have an impact on various domains such as healthcare, business, industry, security, and how all countries around the world are feeling this impact. The book aims at low-cost solutions which could be implemented even in developing countries. It highlights the significant impact these technologies have on various industries and on us as humans. It provides a virtual picture of forthcoming better human life shadowed by the new technologies and their applications and discusses the impact Data Science has on business applications. The book will also include an overview of the different AI applications and their correlation between each other. The audience is graduate and postgraduate students, researchers, academicians, institutions, and professionals who are interested in exploring key technologies like Artificial Intelligence, Machine Learning, and Data Science.