Applied computing in medicine and health /

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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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Al-Jumeily, Dhiya (Editor ), Hussain, Abir (Editor ), Mallucci, Conor (Editor ), Oliver, Carol (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Amsterdam : Elsevier, �2016.
Colección:Emerging topics in computer science and applied computing.
Temas:
Medicine > Data processing.
Medical informatics.
Medical Informatics Applications
Medical Informatics
M�edecine > Informatique.
HEALTH & FITNESS > Holism.
HEALTH & FITNESS > Reference.
MEDICAL > Alternative Medicine.
MEDICAL > Atlases.
MEDICAL > Essays.
MEDICAL > Family & General Practice.
MEDICAL > Holistic Medicine.
MEDICAL > Osteopathy.
Medical informatics
Medicine > Data processing
Acceso en línea:Texto completo
Tabla de Contenidos:
  • 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

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