E-Books →Hands-On Healthcare Data Taming the Complexity of Real-World Data

This book provides pragmatic and hands-on solutions for working with healthcare data, from data extraction to cleaning and harmonization to feature engineering. Author Andrew Nguyen covers specific ML and deep learning examples with a focus on producing high-quality data. You'll discover how graph technologies help you connect disparate data sources so you can solve healthcare's most challenging problems using advanced analytics.
You'll learn
Different types of healthcare dаta: electronic health records, clinical registries and trials, digital health tools, and claims data
The challenges of working with healthcare data, especially when trying to aggregate data from multiple sources
Current options for extracting structured data from clinical text
How to make trade-offs when using tools and frameworks for normalizing structured healthcare data
How to harmonize healthcare data using terminologies, ontologies, and mappings and crosswalks