ksgeist/Merrimack_DSE6630
May 2026 – May 2026
1 Month active
Languages Used
CSVHTMLR
Technical Skills
R programmingdata analysisdata cleaningdata preparationdata visualizationhealthcare analytics
pgyorda
PROFILE
Pgyorda
Worked on the ksgeist/Merrimack_DSE6630 repository to deliver end-to-end analytics and data-processing enhancements focused on healthcare data. Developed a pneumonia readmission analytics framework that included data cleaning, exploratory analysis, feature selection, and predictive clustering, producing HTML reports for stakeholders. Advanced heart failure analytics by preparing final datasets and updating CMS-based modeling, supporting production pipeline readiness. Expanded hospital-level data processing with improved file path handling, robust data cleaning, and enhanced visualizations, while adding new healthcare metrics data files. Used R programming, tidyverse, and data visualization techniques throughout, and improved documentation to clarify dataset selection, including a bug fix for data split guidance.
Overall Statistics
Feature vs Bugs
80%Features
Repository Contributions
10Total
Bugs
1
Commits
10
Features
4
Lines of code
20,689
Activity Months1
Your Network
18 peopleWork History
May 2026
10 Commits • 4 Features
May 1, 2026May 2026 — Delivered end-to-end analytics and data-processing enhancements in ksgeist/Merrimack_DSE6630. Key deliverables spanned pneumonia and heart failure analytics, hospital data processing, and documentation improvements, collectively enabling faster insights, reproducible reporting, and improved risk stratification for patient readmission. Highlights include a pneumonia readmission analytics framework with data cleaning, exploratory analysis, feature selection, and predictive clustering, plus generated HTML reports for stakeholder consumption. Heart failure analytics and datasets advanced with final sample preparation and CMS-based modeling updates, preparing for production data pipelines. Hospital-level data processing was expanded with improved file path handling, data cleaning, visualization enhancements, and new healthcare metrics data files. Documentation improvements clarified dataset selection and usage, and a bug fix addressed a training-to-testing split typo to ensure correct guidance.
10 Commits • 4 Features
May 1, 2026May 2026 — Delivered end-to-end analytics and data-processing enhancements in ksgeist/Merrimack_DSE6630. Key deliverables spanned pneumonia and heart failure analytics, hospital data processing, and documentation improvements, collectively enabling faster insights, reproducible reporting, and improved risk stratification for patient readmission. Highlights include a pneumonia readmission analytics framework with data cleaning, exploratory analysis, feature selection, and predictive clustering, plus generated HTML reports for stakeholder consumption. Heart failure analytics and datasets advanced with final sample preparation and CMS-based modeling updates, preparing for production data pipelines. Hospital-level data processing was expanded with improved file path handling, data cleaning, visualization enhancements, and new healthcare metrics data files. Documentation improvements clarified dataset selection and usage, and a bug fix addressed a training-to-testing split typo to ensure correct guidance.
May 2026
Activity
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Quality Metrics
Correctness94.0%
Maintainability86.0%
Architecture88.0%
Performance84.0%
AI Usage26.0%
Skills & Technologies
Programming Languages
CSVHTMLR
Technical Skills
R programmingdata analysisdata cleaningdata preparationdata visualizationhealthcare analyticshealthcare metricsmachine learningpredictive modelingstatistical analysisstatistical modelingtidyverse
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