Because SNOMED and ICD Codes must be treated as categories for gradient boosting The 8 main blood types (A+, A-, B- rare, B+, O+, O- universal, AB+, AB-) are categories. If I used label encoding then each category becomes integer (e.g A+ =0, B-=1, AB+=2). This is compact but introduces a false ordering and the… Continue reading Using CatBoost.ai in Healthcare
Faster Insight, Better Reuse, and Scalable Data Foundations Healthcare organisations face growing demand for better use of data: improving operational performance, supporting population health management, enabling AI, and accelerating research. Yet many still rely on fragmented pipelines, duplicated transformations, and slow bespoke data requests. At the same time, the economics of technology have changed. Modern… Continue reading Explaining Medallion Data Architectures in Healthcare
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