HELP & FREQUENTLY ASKED QUESTIONS

Frequently Asked Questions

Find clear answers regarding the dataset, clinical scope, Tableau embeds, and platform methodology.

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Health360 is an interactive healthcare intelligence project that pairs epidemiological datasets with Tableau Public visual analytics and a Flask web service. Its primary aim is to reveal meaningful correlations between patient demographics, clinical biomarkers (such as blood pressure, glucose, and BMI), lifestyle behaviors, and chronic illness risks.
The platform specifically analyzes three major chronic conditions: Coronary Heart Disease, Type 2 Diabetes, and Stroke. Key clinical and behavioral indicators evaluated include age, sex, Body Mass Index (BMI), systolic/diastolic blood pressure, fasting glucose, serum cholesterol levels, active smoking status, and physical exercise routines.
No. The visualizations and interactive screening models display population-level descriptive statistics, historical cohort distributions, and empirical correlations. They are not cleared medical diagnostic software and do not replace personalized consultation, diagnostic tests, or advice from qualified healthcare professionals.
The visualizations are designed, published, and hosted directly on Tableau Public Cloud. The web application dynamically connects to Tableau's official Embedding API v3 to load live, interactive views. The site itself does not store or process private medical records (PHI).
Because the charts are streamed live from Tableau Public servers, initial loading may take a few seconds depending on internet bandwidth and Tableau server traffic. If the chart fails to load, ensure JavaScript and third-party scripts are permitted in your browser, or click the "Open in Tableau Public" button on the dashboard page to open the native workbook directly.
Yes! Inside the embedded dashboard, you can click on any chart element, select specific age categories, toggle disease subsets, or click the Tableau toolbar at the bottom of the visualization to download PDFs, images, or crosstab datasets.
The project is structured as a lightweight Python Flask application. Simply run pip install -r requirements.txt followed by python app.py to run locally on port 5000. It also includes a Procfile for one-click deployment on platforms like Render, Heroku, or Railway, as well as a pre-built static version for GitHub Pages.