Data Science for Healthcare: Methodologies and Applications

Part I: Challenges and Basic Technologies.- Data Science in healthcare: benefits, challenges and opportunities.- Introduction to Classification Algorithms and their Performance Analysis using Medical Examples.- The role of deep learning in improving healthcare.- Part II: Specific Technologies and Applications.- Making effective use of healthcare data using data-to-text technology.- Clinical Natural Language Processing with Deep Learning.- Ontology-based Knowledge Management for Comprehensive Geriatric Assessment and Reminiscence Therapy on Social Robots.- Assistive Robots for the elderly: innovative tools to gather health relevant data.- Overview of data linkage methods for integrating separate health data sources.- A Flexible Knowledge-based Architecture For Supporting The Adoption of Healthy Lifestyles with Persuasive Dialogs.- Visual Analytics for Classifier Construction and Evaluation for Medical Data.- Data Visualization in Clinical Practice.- Using process analytics to improve healthcare processes.- A Multi-Scale Computational Approach to Understanding Cancer Metabolism.- Leveraging healthcare financial analytics for improving the health of entire populations.