Advanced Computational Intelligence in Healthcare-7 (Studies in Computational Intelligence, 891)

✍ Scribed by Maglogiannis

• Publisher: Springer
• Year: 2020
• Tongue: English
• Leaves: 169
• Edition: 1st ed. 2020
• Category: Library

✦ Synopsis

This book presents state-of-the-art works and systematic reviews in the emerging field of computational intelligence (CI) in electronic health care. The respective chapters present surveys and practical examples of artificial intelligence applications in the areas of Human-Machine Interface (HMI) and affective computing, machine learning, big health data and visualization analytics, computer vision and medical image analysis. The book also addresses new and emerging topics in CI for health care such as the utilization of Social Media (SM) and the introduction of new intelligent paradigms in the security and privacy domains, which are critical for the health sector. The chapters, while of course not exhaustively addressing all the possible aspects of the aforementioned areas, are indicative of the dynamic nature of interdisciplinary research being pursued. Accordingly, the book is intended not only for researchers in the respective fields, but also for medical and administrative personnel working in the health sector, as well as managers and stakeholders responsible for making strategic decisions and defining public health policies.

✦ Table of Contents

Preface
Contents
Human–Machine Interfaces for Motor Rehabilitation
1 Background
2 Human–Machine Motor Rehabilitation Interfaces
3 Computational Intelligence Tools
4 Non-physiological Modalities
5 Physiological Modalities
6 Future Challenges
References
Passive Emotion Recognition Using Smartphone Sensing Data
1 Introduction
2 Background Information and Related Work
2.1 Emotions
2.2 Related Work
3 Methodology
3.1 Microsoft Emotion API
3.2 Google Fit
4 Experiments
4.1 Data Collection
4.2 Experimental Results
5 Conclusion
6 Future Work
References
Intelligent and Immersive Visual Analytics of Health Data
1 Introduction
2 Visualization for Health Data
3 Visual Artificial Intelligence for Health Data
3.1 Case Study—Rhabdomyosarcoma
4 Immersive Technologies
4.1 Case Study—Immersive Visualization for Cancer Data
5 Discussion
References
Interactive Process Indicators for Obesity Modelling Using Process Mining
1 Introduction
2 Methods
3 Results
3.1 iPI0: Semantic Definition for Dynamic Obesity
3.2 iPI1: Blood Pressure Dynamic Model
4 Discussion and Conclusions
References
Recent Machine Learning Approaches for Single-Cell RNA-seq Data Analysis
1 Introduction
2 Single-Cell Sequencing Data Challenges
2.1 Classification
2.2 Clustering
2.3 Visualization
3 Discussion
References
A Review on State-of-the-Art Computer-Based Approaches for the Early Recognition of Malignant Melanoma
1 Introduction
2 Basic Methods for Melanoma Detection Using a Computer-Based Approach
3 Evaluation of the Basic Methods Using a Computer-Based Approach
4 Diverse Techniques for Melanoma Detection
5 Molecular Techniques for Melanoma Detection
6 Data Integration
7 Discussion
References
Cardiovascular Disease Stratification Based on Ultrasound Images of the Carotid Artery
1 Introduction
2 Materials and Methods
2.1 Recording of Ultrasound Images
2.2 Manual IMT Measurements
2.3 Speckle Reduction Filtering (DsFlsmv)
2.4 Snakes Segmentation
2.5 Cardiovascular Disease Classification Modelling
2.6 Statistical Analysis
3 Results
4 Discussion
References
Forecasting and Prevention Mechanisms Using Social Media in Health Care
1 Introduction
2 Literature Review
2.1 Virus–Illness Outbreaks
2.2 Anti-vaccination
2.3 Mental Health
2.4 Social Trends
2.5 Food and Environment
3 Evaluation of Impact on Science, Economy and Society
3.1 Science Impact
3.2 Economic Impact
3.3 Social Impact
4 Directions for Future Work
5 Conclusion
References
Security and Privacy Issues for Intelligent Cloud-Based Health Systems
1 Introduction
2 Methodology
3 Threats of Cloud-Based Health Systems
4 Attack Scenarios for Specific Threat Groups (Categories of Threats)
5 Cloud-Based Health System’s Objectives and Assets
6 Security and Privacy Solutions in Cloud Health Systems
7 Conclusions
References