Thanh M. Nguyen
BioInformatics, HealthTech, ML, NLP
Welcome to my pages
Data Science
Osteoporosis prediction using machine learning
In this project, I performed EAD on a case-control dataset for osteoporosis, controlling for demographic variables such as age, gender, and ethnicity. Then I built predictive models using LR, RF, SVM, and XGB. The Gradient Boosting Classifier and Logistic Regression achieved the highest ROC scores. Even though this is a balance dataset, the variables tend to be bias towards the negative class (no-osteoporosis), meaning the True Negative and False Negative scores are always higher than True Positive and False Positive scores. This trend is consistent in the confusion matrix of the 6 ML models.
COVID-19 Vaccine adverse symptoms in VAERS with Association Rule Mining
To address vaccine hesitancy issues, I studied the adverse symptoms in COVID-19 vaccines using the VAERS data. VAERS is the public surveillance system co-manage by the CDC and FDA to detect rare vaccine adverse events. By applying association rule mining, I discovered the top adverse symptoms in COVID-19 vaccines, and compared the differences in adverse symptoms between Moderna and Pfizer vaccines.
Visualization app in RShiny using MAUDE dataset
MAUDE is the medical device passive surveillance dataset from the FDA. I built a visualization app to project the temporal trends in the harm levels using the 2016 MAUDE data.