In this repository, we explore the use of BRFSS dataset for descriptive analysis.

According to the CDC, heart disease is one of the leading causes of death for people of most races in the US. Our ML project leads to a better understanding of how we can predict heart disease.

Possible projects on Behavioral Machine Learning

Predictors of Smoking Cessation in the U.S.: A Machine Learning Analysis Revealing the Socioeconomic Paradox in BRFSS Data (2018-2023)

Analysis of 2023 BRFSS data exploring the relationship between insurance status, flu shot uptake, and preventive care access. Includes data cleaning, EDA, logistic regression, and visualizations using R (tidyverse, caret, broom). Data from CDC BRFSS 2023.

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.

State-Level Risk Factor Analysis of Mental Health Wellbeing

Final Project for Coursera [Introduction to probability and Data with R] by Duke University

Predicting self-reported health in seniors who participated in the Behavioral Risk Factor Surveillance System (CRFSS) 2015 Survey.

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)

Using the 2023 BRFSS Survey Data to explore the relationship between reported exercise habits and reported mental health