Data Scientist at John Snow Labs specializing in Clinical NLP and production-grade healthcare AI systems. I build and optimize NLP pipelines for NER, de-identification (DEID), medical code system mapping, and clinical data standardization, transforming unstructured clinical text into structured, interoperable datasets. My work leverages healthcare standards such as UMLS, SNOMED CT, ICD-10, LOINC, RxNORM, HL7 FHIR, and OMOP to enable scalable, real-world clinical data solutions.
TL; DR This post presents a focused update on large-scale clinical de-identification benchmarks, emphasizing pipeline design, execution strategy, and infrastructure-aware performance. Rather than treating accuracy as an isolated metric, we...
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