This project aims to compare traditional Machine Learning methods for tabular data classification, such as Ensemble methods, Decision Trees, and Naive Bayes, with NLP classification methods like Multinomial Naive Bayes, RNNs, and Transformers. We are utilizing survey data from the CDC via the Behavioral Risk Factor Surveillance System (BRFSS)

Code and models for our ICACIE2019 paper "Prediction of Stroke Risk Factors for Better Pre-emptive Healthcare: A Public-Survey-Based Approach"

Data analysis project in R

US College Educated Population vs Geographic Mobility from Abroad

Exploratory Data Analysis of the 2013 BRFSS Data

Data analysis project using R and R Studio and data from the 2013 Behavioral Risk Factor Surveillance System (BRFSS).

Based on telephone health survey data from the CDC

Mental Health Prediction using BRFSS 2021

Primeiro projeto apresentado na disciplina de Inteligência Computacional em Saúde utilizando a base de dados de indicadores de saúde para tarefa de classificação de indivíduos com diabetes.

Final Project for COGS108 (Data Science in Practice) at UCSD - PCA-based health index for the United States

Association between insurance, PCP, and chronic illness diagnosis in BRFSS

BRFSS-2021 data was used to build a linear regression model to predict BMI & a logistic regression model to predict ACEs exposure in adults 18-79 living in the southern United States

Cross-sectional analysis of the association between poor mental health days, healthcare access and cannabis in WA State using BRFSS data from the CDC.

Behavioral Risk Factor Surveillance System (BRFSS) data, 2014-2020