Includes bibliographical references and index.

1. Early diagnosis of neurodegenerative diseases from gait discrimination to neural synchronization -- 2. Lifelogging technologies to detect negative emotions associated with cardiovascular disease -- 3. Gene selection methods for microarray data -- 4. Brain MRI intensity inhomogeneity correction using region of interest, anatomic structural map, and outlier detection -- 5. Leveraging big data analytics for personalized elderly care: opportunities and challenges -- 6. Prediction of intrapartum hypoxia from cardiotocography data using machine learning -- 7. Recurrent neural networks in medical data analysis and classifications -- 8. Assured decision and meta-governance for mobile medical support systems -- 9. Identifying preferences and developing an interactive data model and assessment for an intelligent mobile application to manage young patients diagnosed with hydrocephalus -- 10. Sociocultural and technological barriers across all phases of implementation for mobile health in developing countries -- 11. Application of real-valued negative selection algorithm to improve medical diagnosis -- 12. Development and applications of mobile farming information system for food traceability in health management -- 13. Telehealth in primary health care: analysis of Liverpool NHS experience -- 14. Swarm based-artificial neural system for human health data classification.

"Applied computing in medicine and health is intended as a comprehensive presentation of ongoing investigations and analysis of current challenges and advances related to applied computing by focusing on a particular class of applications, primarily artificial intelligence methods and techniques in health and medicine." -- Back cover. 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.