Applied computing in medicine and health /
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 com...
Call Number: | Libro Electrónico |
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Other Authors: | , , , |
Format: | Electronic eBook |
Language: | Inglés |
Published: |
Amsterdam :
Elsevier,
�2016.
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Series: | Emerging topics in computer science and applied computing.
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Subjects: | |
Online Access: | Texto completo |
Table of Contents:
- THE ORGANIZATION OF THE BOOKChapter 1
- Early Diagnosis of Neurodegenerative Diseases from Gait Discrimination to Neural Synchronization
- INTRODUCTION
- RESEARCH CHALLENGES
- NEURODEGENERATIVE DISEASES
- CLASSIFICATION ALGORITHMS FOR NDDS
- NEURAL SYNCHRONIZATION AND DATA COLLECTION
- NEURAL SYNCHRONY MEASUREMENT TECHNIQUE
- DATA DESCRIPTION AND DATA FILTERING
- DIFFERENT APPROACHES TO COMPUTE EEG SYNCHRONY
- STATISTICAL ANALYSIS
- CONCLUSION
- REFERENCES
- Chapter 2
- Lifelogging Technologies to Detect Negative Emotions Associated with Cardiovascular DiseaseINTRODUCTION
- BACKGROUND
- RESEARCH CHALLENGES
- SUMMARY
- Acknowledgements
- REFERENCES
- Chapter 3
- Gene Selection Methods for Microarray Data
- INTRODUCTION TO GENE SELECTION
- FEATURE SELECTION ALGORITHMS BASED ON WRAPPER APPROACH
- UNSUPERVISED FILTER BASED FEATURE SELECTION ALGORITHMS
- CONCLUSIONS
- REFERENCES
- Chapter 4
- Brain MRI Intensity Inhomogeneity Correction Using Region of Interest, Anatomic Structural Map, and Outlier Det ...
- INTRODUCTIONMATHEMATICAL MODELS OF BIAS FIELD
- DESIGN TECHNIQUES OF CURRENT ALGORITHMS
- IMPORTANCE OF CURRENT ALGORITHMS
- METHODS
- EXPERIMENTAL DESIGN
- DISCUSSION
- CONCLUSION
- REFERENCES
- Chapter 5
- Leveraging Big Data Analytics for Personalized Elderly Care: Opportunities and Challenges
- INTRODUCTION
- THE CHALLENGE OF PERSONALIZATION IN ELDERLY CARE
- BIG DATA ANALYTICS FOR ELDERLY CARE
- PROPOSED FRAMEWORK
- EXAMPLE SCENARIO
- DISCUSSION AND CONCLUSION
- REFERENCES
- Chapter 6
- Prediction of Intrapartum Hypoxia from Cardiotocography Data Using Machine LearningINTRODUCTION
- MONITORING INTRAPARTUM FETAL HYPOXIA
- AMBULATORY CTG MONITORING
- PROPOSED METHODOLOGY
- FUTURE RESEARCH DIRECTIONS
- CONCLUSIONS
- REFERENCES
- Chapter 7
- Recurrent Neural Networks in Medical Data Analysis and Classifications
- INTRODUCTION
- MEDICAL DATA PREPROCESSING
- CLASSIFICATION
- RNNS FOR CLASSIFICATION
- INTRODUCTION TO PRETERM
- ELECTROHYSTEROGRAM
- UTERINE EHG SIGNAL PROCESSING
- MODELING RNN FOR FORECASTING