🩺 Diabetes Risk Prediction Dashboard

Interactive analysis of health indicators from BRFSS 2015 dataset

🩺 Diabetes Risk Prediction Dashboard

Cross-Country Analysis: US (BRFSS) & Canada (CCHS) Health Data

📊 Cross-Country Dataset Overview

This dashboard analyzes diabetes risk factors using two major health survey datasets from North America:

🇺🇸 US Dataset (BRFSS 2015)

253,680 records

Behavioral Risk Factor Surveillance System

All 50 US states, DC, and territories

🇨🇦 Canadian Dataset (CCHS)

108,252 records

Canadian Community Health Survey

All Canadian provinces and territories

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Total Records

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Diabetes Cases

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Average BMI

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High BP Rate

Diabetes Status Distribution

Feature Correlation with Diabetes

🔍 Exploratory Data Analysis

Interactive analysis of health indicators and their relationships with diabetes.

BMI Distribution by Diabetes Status

Age Distribution by Diabetes Status

Risk Factor Prevalence

🤖 Cross-Country Model Performance

Machine learning models trained and validated on both US and Canadian datasets for robust diabetes prediction.

📊 Model Performance Comparison (ROC-AUC Scores)

Model 🇺🇸 US (BRFSS) 🇨🇦 Canada (CCHS) Performance Gap
Logistic Regression 0.8149 0.7729 +0.0420
Random Forest 0.7913 0.7055 +0.0858
XGBoost 0.8206 0.7315 +0.0891

0.815

Best US Model (XGBoost)

0.773

Best Canada Model (Logistic)

Cross-Validated

Both Countries

Model Performance Comparison

Feature Importance (XGBoost)

🔮 Cross-Country Diabetes Risk Prediction

Enter your health information to get a personalized diabetes risk assessment based on both US and Canadian health data.

🌍 Cross-Country Validation

This prediction model is trained on 361,932 health records from both the United States and Canada, providing robust and validated risk assessment.

🏥 Medical History

🚬 Lifestyle Factors

🥗 Diet

👤 Demographics