This repo is the Machine Learning practice on NHANES dataset of Heart Disease prediction. The ML algorithms like LR, DT, RF, SVM, KNN, NB, MLP, AdaBoost, XGBoost, CatBoost, LightGBM, ExtraTree, etc. The results are good. I also explore the class-balancing (SMOTE) because the original dataset contains only 5% of patient and 95% of healthy record.

Analysis of BMI and its relationship with sleep disorders, blood pressure, and smoking using the NHANES 2017-2018 dataset, with R for statistical Modeling.

Jupyter Notebook with R

Objective, create an intuitive and user-friendly web-based application for visualizing and exploring NHANES data. This dashboard will enable users, including those with limited or no Python programming experience, to interact with NHANES data and generate informative visualizations to gain insights into various health-related aspects.

Possible projects on Behavioral Machine Learning

This project aims to conduct a thorough Exploratory Data Analysis (EDA) using NHANES Demographic and Questionnaire Data to investigate and gain an understanding on health disparities & Inequities in the U.S. Our goal is to identify the key factors contributing to health disparities and provide insights for promoting health equity.

Develop machine learning models that detect diseases from blood test data. Utilizing machine learning, it analyzes patterns and predicts potential health conditions, offering users early insights for proactive care.