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Chapter 1 - Early Diagnosis of Neurodegenerative Diseases from Gait Discrimination to Neural Synchronization
Shamaila Iram, Francois-Benoit Vialatte and Muhammad Irfan Qamar
Pages 1-26 - Book chapterAbstract only
Chapter 2 - Lifelogging Technologies to Detect Negative Emotions Associated with Cardiovascular Disease
Chelsea Dobbins and Stephen Fairclough
Pages 27-44 - Book chapterAbstract only
Chapter 3 - Gene Selection Methods for Microarray Data
B. Chandra
Pages 45-78 - Book chapterAbstract only
Chapter 4 - Brain MRI Intensity Inhomogeneity Correction Using Region of Interest, Anatomic Structural Map, and Outlier Detection
Michael Osadebey, Nizar Bouguila and Douglas Arnold
Pages 79-98 - Book chapterAbstract only
Chapter 5 - Leveraging Big Data Analytics for Personalized Elderly Care: Opportunities and Challenges
Obinna Anya and Hissam Tawfik
Pages 99-124 - Book chapterAbstract only
Chapter 6 - Prediction of Intrapartum Hypoxia from Cardiotocography Data Using Machine Learning
Paul Fergus, De-Shuang Huang and Hani Hamdan
Pages 125-146 - Book chapterAbstract only
Chapter 7 - Recurrent Neural Networks in Medical Data Analysis and Classifications
Haya Al-Askar, Naeem Radi and Áine MacDermott
Pages 147-165 - Book chapterAbstract only
Chapter 8 - Assured Decision and Meta-Governance for Mobile Medical Support Systems
Martin Randles, Princy Johnson and Naeem Radi
Pages 166-182 - Book chapterAbstract only
Chapter 9 - Identifying Preferences and Developing an Interactive Data Model and Assessment for an Intelligent Mobile Application to Manage Young Patients Diagnosed with Hydrocephalus
Anthony Farrugia, Stephen Attard, ... Ali Ghuname
Pages 183-211 - Book chapterAbstract only
Chapter 10 - Sociocultural and Technological Barriers Across all Phases of Implementation for Mobile Health in Developing Countries
Yvonne O’ Connor, Siobhan O’ Connor, ... John O’ Donoghue
Pages 212-230 - Book chapterAbstract only
Chapter 11 - Application of Real-Valued Negative Selection Algorithm to Improve Medical Diagnosis
Ayodele Lasisi, Rozaida Ghazali and Tutut Herawan
Pages 231-243 - Book chapterAbstract only
Chapter 12 - Development and Applications of Mobile Farming Information System for Food Traceability in Health Management
Yu-Chuan Liu and Hong-Mei Gao
Pages 244-268 - Book chapterAbstract only
Chapter 13 - Telehealth in Primary Health Care: Analysis of Liverpool NHS Experience
Nonso Nnamoko, Farath Arshad, ... Pat Patterson
Pages 269-286 - Book chapterAbstract only
Chapter 14 - Swarm Based-Artificial Neural System for Human Health Data Classification
Habib Shah, Rozaida Ghazali, ... Nawsher Khan
Pages 287-309 - Book chapterNo access
Index
Pages 311-317
About the book
Description
Applied Computing in Medicine and Health is a comprehensive presentation of on-going investigations into current applied computing challenges and advances, with a focus on a particular class of applications, primarily artificial intelligence methods and techniques in medicine and health.
Applied computing is the use of practical computer science knowledge to enable use of the latest technology and techniques in a variety of different fields ranging from business to scientific research. One of the most important and relevant areas in applied computing is the use of artificial intelligence (AI) in health and medicine. Artificial intelligence in health and medicine (AIHM) is assuming the challenge of creating and distributing tools that can support medical doctors and specialists in new endeavors. The material included covers a wide variety of interdisciplinary perspectives concerning the theory and practice of applied computing in medicine, human biology, and health care.
Particular attention is given to AI-based clinical decision-making, medical knowledge engineering, knowledge-based systems in medical education and research, intelligent medical information systems, intelligent databases, intelligent devices and instruments, medical AI tools, reasoning and metareasoning in medicine, and methodological, philosophical, ethical, and intelligent medical data analysis.
Applied Computing in Medicine and Health is a comprehensive presentation of on-going investigations into current applied computing challenges and advances, with a focus on a particular class of applications, primarily artificial intelligence methods and techniques in medicine and health.
Applied computing is the use of practical computer science knowledge to enable use of the latest technology and techniques in a variety of different fields ranging from business to scientific research. One of the most important and relevant areas in applied computing is the use of artificial intelligence (AI) in health and medicine. Artificial intelligence in health and medicine (AIHM) is assuming the challenge of creating and distributing tools that can support medical doctors and specialists in new endeavors. The material included covers a wide variety of interdisciplinary perspectives concerning the theory and practice of applied computing in medicine, human biology, and health care.
Particular attention is given to AI-based clinical decision-making, medical knowledge engineering, knowledge-based systems in medical education and research, intelligent medical information systems, intelligent databases, intelligent devices and instruments, medical AI tools, reasoning and metareasoning in medicine, and methodological, philosophical, ethical, and intelligent medical data analysis.
Key Features
- Discusses applications of artificial intelligence in medical data analysis and classifications
- Provides an overview of mobile health and telemedicine with specific examples and case studies
- Explains how behavioral intervention technologies use smart phones to support a patient centered approach
- Covers the design and implementation of medical decision support systems in clinical practice using an applied case study approach
- Discusses applications of artificial intelligence in medical data analysis and classifications
- Provides an overview of mobile health and telemedicine with specific examples and case studies
- Explains how behavioral intervention technologies use smart phones to support a patient centered approach
- Covers the design and implementation of medical decision support systems in clinical practice using an applied case study approach
Details
ISBN
978-0-12-803468-2
Language
English
Published
2016
Copyright
Copyright © 2016 Elsevier Inc. All rights reserved.
Imprint
Morgan Kaufmann