- Explains the design of organized, semi-structured, unstructured, and irregular time series data of electronic health records
- Covers information extraction, standards for meta-data, reuse of metadata for clinical research, and organized and unstructured data
- Discusses supervised and unsupervised learning in electronic health records
- Describes clustering and classification techniques for organized, semi- structured, and unstructured data from electronic health records
This book is an essential resource for researchers and professionals in fields like computer science, biomedical engineering, and information technology, seeking to enhance healthcare efficiency, security, and privacy through advanced data analytics and machine learning.
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