The Center for Health Statistics (CHS) collects and analyzes vital records and hospitalization data. The Data Science and Engineering Unit in CHS unit performs analyses on a variety of topics that interact with these data.
We publish findings, methodological advancements and analyses via DOH reports and peer-reviewed studies. Several areas of interest have been established with the intent of disseminating information to interested audiences.
Data Linkage Methodology
The Data Science and Engineering Unit specializes in large scale machine learning data linkages. The unit emphasizes equitable representation and accuracy in linkage practices.
- Prioritizing Equitable Representation, Sustainability, and Accuracy: The Deployment of Machine Learning Linkage Strategies During the COVID-19 Pandemic (PDF)
- Improving COVID-19 Case and Immunization Record Linkage via Non-Probabilistic Machine Learning-Based Classification (2023 CSTE Outstanding Poster Award Winner, PDF)
- Supervised Machine Learning Linkage: A Demo and Evaluation of Project ECHIDNA (PDF)
- Introduction to Machine Learning (Vimeo)
Data Science, Statistics, and Analyses
CHS performs independent and collaborative analyses that involve vital record and hospitalization data. Reports produced by data scientists span multiple research topics.