Hands-On Healthcare Data: Taming the Complexity of Real-World Data #
- Book: https://www.oreilly.com/library/view/hands-on-healthcare-data/9781098112912/
- Code: https://gitlab.com/hands-on-healthcare-data
| Chapter | Summary |
|---|---|
| 1. Introduction to Healthcare Data Overview of data types (EHR, claims, registries, trials) and enterprise challenges. |
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| 2. Technical Introduction Covers Docker, database systems, and data architecture. |
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| 3. Standardized Vocabularies in Healthcare Discusses vocabularies like SNOMED, ICD, UMLS and their usage. |
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| 4. Deep Dive: Electronic Health Records Data Explores MIMIC, Synthea, and normalization issues in EHRs. |
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| 5. Deep Dive: Claims Data Analysis of claims datasets like SynPUF and integration strategies. |
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| 6. Machine Learning and Analytics Feature engineering, graph-based ML, embeddings, SQL vs. graph ops. |
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| 7. Trends in Healthcare Analytics Federated learning, NLP in healthcare, and harmonization trends. |
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| 8. Harmonization, and Final Thoughts RWD diversity, business-technical gap, graph limitations. |