Applied Computing in Medicine and Health
- 366 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Applied Computing in Medicine and Health
About This Book
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.
- 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
Frequently asked questions
Information
Early Diagnosis of Neurodegenerative Diseases from Gait Discrimination to Neural Synchronization
E-mail: [email protected], [email protected], [email protected]
Abstract
Keywords
Combining Classifiers; Pattern Recognition; Machine Learning; Behavior classification; Neurodegenerative Diseases; Movement Signals; Electroencephalographic Signals; Neural Synchronization; Cross-correlation; Phase synchrony; Coherence; MannâWhitney U TestIntroduction
Table of contents
- Cover image
- Title page
- Table of Contents
- Copyright
- List of Contributors
- Editor Biographies
- Author Biographies
- Acknowledgment
- Introduction
- Chapter 1. Early Diagnosis of Neurodegenerative Diseases from Gait Discrimination to Neural Synchronization
- Chapter 2. Lifelogging Technologies to Detect Negative Emotions Associated with Cardiovascular Disease
- Chapter 3. Gene Selection Methods for Microarray Data
- Chapter 4. Brain MRI Intensity Inhomogeneity Correction Using Region of Interest, Anatomic Structural Map, and Outlier Detection
- Chapter 5. Leveraging Big Data Analytics for Personalized Elderly Care: Opportunities and Challenges
- Chapter 6. Prediction of Intrapartum Hypoxia from Cardiotocography Data Using Machine Learning
- Chapter 7. Recurrent Neural Networks in Medical Data Analysis and Classifications
- Chapter 8. Assured Decision and Meta-Governance for Mobile Medical Support Systems
- Chapter 9. Identifying Preferences and Developing an Interactive Data Model and Assessment for an Intelligent Mobile Application to Manage Young Patients Diagnosed with Hydrocephalus
- Chapter 10. Sociocultural and Technological Barriers Across all Phases of Implementation for Mobile Health in Developing Countries
- Chapter 11. Application of Real-Valued Negative Selection Algorithm to Improve Medical Diagnosis
- Chapter 12. Development and Applications of Mobile Farming Information System for Food Traceability in Health Management
- Chapter 13. Telehealth in Primary Health Care: Analysis of Liverpool NHS Experience
- Chapter 14. Swarm Based-Artificial Neural System for Human Health Data Classification
- Index