From Complex Data to Meaningful Evidence
This selected analytics experience involved large U.S. healthcare discharge datasets comprising millions of healthcare records, with Lyme disease cases identified through ICD-10-based methods. The work included data preparation, cleaning, and validation, followed by demographic, geographic, seasonal, and socioeconomic pattern analysis.
A subsequent machine-learning analysis extended the work to approximately 4.8 million healthcare records evaluated across 7 analytical models, with statistical analysis, model comparison, visualization, and interpretation supporting the findings.