Reproducible research systems
Traceable workflows connecting protocols, data dictionaries, analytical code, quality checks, results, and reporting.
Permanent author profile
Dr. Andrie Udal
PhD, MSHDS
Healthcare Data Science Lead, ProWrite
Dr. Andrie Udal, PhD, MSHDS leads ProWrite's healthcare data science work. His scope includes reproducible research workflows, applied machine learning, and real-world evidence design, connecting clinical questions with defensible data methods and clear, researcher-owned scientific communication.
Areas of focus
Turning complex data into research that can be checked.
Applied health data science
Practical statistical and machine-learning approaches grounded in clinical questions, data limitations, and appropriate validation.
Real-world evidence
Study designs and analytical reasoning for observational health data, with explicit attention to bias, uncertainty, and generalizability.
Recent author publication
Practical guidance for defensible medical research.
A Model Output Is Not Valid Until Its Assumptions Are Checked
A practical framework for identifying, checking, documenting, and stress-testing the assumptions behind a primary statistical model.
Read the article →