[PDF] Computational Technology For Effective Health Care eBook

Author : National Research Council
Publisher : National Academies Press
Page : 121 pages
File Size : 10,29 MB
Release : 2009-02-24
Category : Computers
ISBN : 0309155843

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Despite a strong commitment to delivering quality health care, persistent problems involving medical errors and ineffective treatment continue to plague the industry. Many of these problems are the consequence of poor information and technology (IT) capabilities, and most importantly, the lack cognitive IT support. Clinicians spend a great deal of time sifting through large amounts of raw data, when, ideally, IT systems would place raw data into context with current medical knowledge to provide clinicians with computer models that depict the health status of the patient. Computational Technology for Effective Health Care advocates re-balancing the portfolio of investments in health care IT to place a greater emphasis on providing cognitive support for health care providers, patients, and family caregivers; observing proven principles for success in designing and implementing IT; and accelerating research related to health care in the computer and social sciences and in health/biomedical informatics. Health care professionals, patient safety advocates, as well as IT specialists and engineers, will find this book a useful tool in preparation for crossing the health care IT chasm.

Author : Committee on Engaging the Computer Science Research Community in Health Care Informatics
Publisher :
Page : 120 pages
File Size : 45,37 MB
Release : 2009-02-24
Category :
ISBN : 9780309386999

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Despite a strong commitment to delivering quality health care, persistent problems involving medical errors and ineffective treatment continue to plague the industry. Many of these problems are the consequence of poor information and technology (IT) capabilities, and most importantly, the lack cognitive IT support. Clinicians spend a great deal of time sifting through large amounts of raw data, when, ideally, IT systems would place raw data into context with current medical knowledge to provide clinicians with computer models that depict the health status of the patient. Computational Technology for Effective Health Care advocates re-balancing the portfolio of investments in health care IT to place a greater emphasis on providing cognitive support for health care providers, patients, and family caregivers; observing proven principles for success in designing and implementing IT; and accelerating research related to health care in the computer and social sciences and in health/biomedical informatics. Health care professionals, patient safety advocates, as well as IT specialists and engineers, will find this book a useful tool in preparation for crossing the health care IT chasm.

Author : Om Prakash Jena
Publisher : John Wiley & Sons
Page : 434 pages
File Size : 25,57 MB
Release : 2021-10-19
Category : Computers
ISBN : 1119818680

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COMPUTATIONAL INTELLIGENCE and HEALTHCARE INFORMATICS The book provides the state-of-the-art innovation, research, design, and implements methodological and algorithmic solutions to data processing problems, designing and analysing evolving trends in health informatics, intelligent disease prediction, and computer-aided diagnosis. Computational intelligence (CI) refers to the ability of computers to accomplish tasks that are normally completed by intelligent beings such as humans and animals. With the rapid advance of technology, artificial intelligence (AI) techniques are being effectively used in the fields of health to improve the efficiency of treatments, avoid the risk of false diagnoses, make therapeutic decisions, and predict the outcome in many clinical scenarios. Modern health treatments are faced with the challenge of acquiring, analyzing and applying the large amount of knowledge necessary to solve complex problems. Computational intelligence in healthcare mainly uses computer techniques to perform clinical diagnoses and suggest treatments. In the present scenario of computing, CI tools present adaptive mechanisms that permit the understanding of data in difficult and changing environments. The desired results of CI technologies profit medical fields by assembling patients with the same types of diseases or fitness problems so that healthcare facilities can provide effectual treatments. This book starts with the fundamentals of computer intelligence and the techniques and procedures associated with it. Contained in this book are state-of-the-art methods of computational intelligence and other allied techniques used in the healthcare system, as well as advances in different CI methods that will confront the problem of effective data analysis and storage faced by healthcare institutions. The objective of this book is to provide researchers with a platform encompassing state-of-the-art innovations; research and design; implementation of methodological and algorithmic solutions to data processing problems; and the design and analysis of evolving trends in health informatics, intelligent disease prediction and computer-aided diagnosis. Audience The book is of interest to artificial intelligence and biomedical scientists, researchers, engineers and students in various settings such as pharmaceutical & biotechnology companies, virtual assistants developing companies, medical imaging & diagnostics centers, wearable device designers, healthcare assistance robot manufacturers, precision medicine testers, hospital management, and researchers working in healthcare system.

Author : Ripon Patgiri
Publisher : Springer Nature
Page : 384 pages
File Size : 26,30 MB
Release : 2021-01-30
Category : Technology & Engineering
ISBN : 9811597359

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This book presents innovative research works to demonstrate the potential and the advancements of computing approaches to utilize healthcare centric and medical datasets in solving complex healthcare problems. Computing technique is one of the key technologies that are being currently used to perform medical diagnostics in the healthcare domain, thanks to the abundance of medical data being generated and collected. Nowadays, medical data is available in many different forms like MRI images, CT scan images, EHR data, test reports, histopathological data and doctor patient conversation data. This opens up huge opportunities for the application of computing techniques, to derive data-driven models that can be of very high utility, in terms of providing effective treatment to patients. Moreover, machine learning algorithms can uncover hidden patterns and relationships present in medical datasets, which are too complex to uncover, if a data-driven approach is not taken. With the help of computing systems, today, it is possible for researchers to predict an accurate medical diagnosis for new patients, using models built from previous patient data. Apart from automatic diagnostic tasks, computing techniques have also been applied in the process of drug discovery, by which a lot of time and money can be saved. Utilization of genomic data using various computing techniques is another emerging area, which may in fact be the key to fulfilling the dream of personalized medications. Medical prognostics is another area in which machine learning has shown great promise recently, where automatic prognostic models are being built that can predict the progress of the disease, as well as can suggest the potential treatment paths to get ahead of the disease progression.

Author : Adam Bohr
Publisher : Academic Press
Page : 385 pages
File Size : 50,30 MB
Release : 2020-06-21
Category : Computers
ISBN : 0128184396

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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

Author : Elio Spinello
Publisher :
Page : 251 pages
File Size : 28,42 MB
Release : 2018
Category : Medical care
ISBN : 9781516515820

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The second edition of Computer Technology for Health Professionals: A Guide to Effective Use and Best Practices bridges the "why" and the "how" of desktop computer technology. This introductory book provides easy to understand explanations of commonly used desktop hardware and software technology within the context of its use in the fields of clinical healthcare and public health practice. Step-by-step instruction on the use of software tools is included, as well as an emphasis on best practices for their use in healthcare and public health organizations. Topics include legal issues for computer users in health-related fields, hardware, software, malware, electronic spreadsheets, data visualization, and relational database management using Microsoft Office. The book also addresses health-related literature research using literature databases, as well as web search engines, with a focus on assessing the scientific validity of health information found online. Readers will also learn about Boolean Logic as it is applied to relational databases and online literature searches, organizational decision-making for the selection and purchase of software, as well as Geographic Information Systems. Each chapter features an "Apply Your Knowledge" section with hands-on exercises that allow readers to immediately implement concepts and skills. Computer Technology for Health Professionals is a common sense approach to using both hardware and software. The book is written for introductory courses in computer proficiency in the fields of the health sciences and public health. Practicing professionals can use the text as a refresher or to bolster skills in specific computer applications.

Author : Hari Singh
Publisher : CRC Press
Page : 225 pages
File Size : 47,85 MB
Release : 2022-07-29
Category : Computers
ISBN : 1000618838

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Data Science for Effective Healthcare Systems has a prime focus on the importance of data science in the healthcare domain. Various applications of data science in the health care domain have been studied to find possible solutions. In this period of COVID-19 pandemic data science and allied areas plays a vital role to deal with various aspect of health care. Image processing, detection & prevention from COVID-19 virus, drug discovery, early prediction, and prevention of diseases are some thrust areas where data science has proven to be indispensable. Key Features: The book offers comprehensive coverage of the most essential topics, including: Big Data Analytics, Applications & Challenges in Healthcare Descriptive, Predictive and Prescriptive Analytics in Healthcare Artificial Intelligence, Machine Learning, Deep Learning and IoT in Healthcare Data Science in Covid-19, Diabetes, Coronary Heart Diseases, Breast Cancer, Brain Tumor The aim of this book is also to provide the future scope of these technologies in the health care domain. Last but not the least, this book will surely benefit research scholar, persons associated with healthcare, faculty, research organizations, and students to get insights into these emerging technologies in the healthcare domain.

Author : Jitendra Kumar Verma
Publisher : Academic Press
Page : 258 pages
File Size : 29,76 MB
Release : 2020-08-01
Category : Science
ISBN : 0128206195

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Computational Intelligence and Its Applications in Healthcare presents rapidly growing applications of computational intelligence for healthcare systems, including intelligent synthetic characters, man-machine interface, menu generators, user acceptance analysis, pictures archiving, and communication systems. Computational intelligence is the study of the design of intelligent agents, which are systems that act intelligently: they do what they think are appropriate for their circumstances and goals; they're flexible to changing environments and goals; they learn from experience; and they make appropriate choices given perceptual limitations and finite computation. Computational intelligence paradigms offer many advantages in maintaining and enhancing the field of healthcare. Provides coverage of fuzzy logic, neural networks, evolutionary computation, learning theory, probabilistic methods, telemedicine, and robotics applications Includes coverage of artificial intelligence and biological applications, soft computing, image and signal processing, and genetic algorithms Presents the latest developments in computational methods in healthcare Bridges the gap between obsolete literature and current literature

Author : Sean Ekins
Publisher : John Wiley & Sons
Page : 462 pages
File Size : 17,36 MB
Release : 2011-08-04
Category : Science
ISBN : 1118026020

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Methods, Processes, and Tools for Collaboration "The time has come to fundamentally rethink how we handle the building of knowledge in biomedical sciences today. This book describes how the computational sciences have transformed into being a key knowledge broker, able to integrate and operate across divergent data types." Bryn Williams-Jones, Associate Research Fellow, Pfizer The pharmaceutical industry utilizes an extended network of partner organizations in order to discover and develop new drugs, however there is currently little guidance for managing information and resources across collaborations. Featuring contributions from the leading experts in a range of industries, Collaborative Computational Technologies for Biomedical Research provides information that will help organizations make critical decisions about managing partnerships, including: Serving as a user manual for collaborations Tackling real problems from both human collaborative and data and informatics perspectives Providing case histories of biomedical collaborations and technology-specific chapters that balance technological depth with accessibility for the non-specialist reader A must-read for anyone working in the pharmaceuticals industry or academia, this book marks a major step towards widespread collaboration facilitated by computational technologies.

Author : Amit Kumar Tyagi
Publisher : John Wiley & Sons
Page : 532 pages
File Size : 28,76 MB
Release : 2021-08-24
Category : Computers
ISBN : 1119785723

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The book details deep learning models like ANN, RNN, LSTM, in many industrial sectors such as transportation, healthcare, military, agriculture, with valid and effective results, which will help researchers find solutions to their deep learning research problems. We have entered the era of smart world devices, where robots or machines are being used in most applications to solve real-world problems. These smart machines/devices reduce the burden on doctors, which in turn make their lives easier and the lives of their patients better, thereby increasing patient longevity, which is the ultimate goal of computer vision. Therefore, the goal in writing this book is to attempt to provide complete information on reliable deep learning models required for e-healthcare applications. Ways in which deep learning can enhance healthcare images or text data for making useful decisions are discussed. Also presented are reliable deep learning models, such as neural networks, convolutional neural networks, backpropagation, and recurrent neural networks, which are increasingly being used in medical image processing, including for colorization of black and white X-ray images, automatic machine translation images, object classification in photographs/images (CT scans), character or useful generation (ECG), image caption generation, etc. Hence, reliable deep learning methods for the perception or production of better results are a necessity for highly effective e-healthcare applications. Currently, the most difficult data-related problem that needs to be solved concerns the rapid increase of data occurring each day via billions of smart devices. To address the growing amount of data in healthcare applications, challenges such as not having standard tools, efficient algorithms, and a sufficient number of skilled data scientists need to be overcome. Hence, there is growing interest in investigating deep learning models and their use in e-healthcare applications. Audience Researchers in artificial intelligence, big data, computer science, and electronic engineering, as well as industry engineers in transportation, healthcare, biomedicine, military, agriculture.