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

Visualized 2015 U.S. health survey data to uncover risk factors and patterns associated with diabetes.

Educational diabetes risk awareness web app — XGBoost model trained on BRFSS big data (2020–2024) using Google BigQuery & Cloud Storage + personalized prevention advice powered by Gemini 2.5-flash. Built with Streamlit. For Canada / North America.

Data analysis project using R and R Studio and data from the 2013 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"

Mental Health Prediction using BRFSS 2021

This project analyses the 2015 BRFSS health survey to identify key predictors of diabetes risk using data cleaning, statistical analysis, and machine‑learning models. BRFSS stands for Behavioral Risk Factor Surveillance System — a large, annual telephone‑based health survey run by the U.S. Centers for Disease Control and Prevention (CDC).

Analysis of CDC BRFSS 2022 data exploring how sleep duration relates to mental and physical health outcomes.

US College Educated Population vs Geographic Mobility from Abroad

Data analysis project in R

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)

Exploratory Data Analysis of the 2013 BRFSS Data

Based on telephone health survey data from the CDC

Survey-weighted statistical analysis of CDC BRFSS 2015 health data using R

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.

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

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

Heart attack risk prediction using the 2011 BRFSS dataset (506k records) with H2O AutoML, imbalance handling strategies, feature selection and precision-recall optimization for clinical risk detection.

Strategic EDA on 253K BRFSS survey responses identifying modifiable vs non-modifiable heart disease risk factors using Python, Pandas, and advanced statistical analysis.

Predicting diabetes risk from BRFSS health indicators with interpretable ML, threshold optimization, and bias/subgroup analysis.