Predicting the
Silent Killer
An end-to-end AI pipeline engineered to detect cardiovascular disease with 73.6%+ accuracy
Our Mission
How It Works
Just like a doctor checks your vitals, our system cleans and organizes the data to ensure accuracy:
- ✓ Smart Formatting: We convert all measurements into a standard format so nothing gets lost in translation.
- ✓ Error Checking: We automatically filter out mistakes, like impossible blood pressure readings.
- ✓ Fair Testing: We kept 20% of our data hidden to strictly test the AI's final performance.
Smart Analysis
The AI doesn't just guess; it calculates new health indicators to get a better picture:
Project Retrospective
A comprehensive analysis of our end-to-end journey to build a robust diagnostic AI.
1.0 Project Overview
This retrospective covers our complete lifecycle from initial data preparation to final model selection. Our primary objective was to build a robust classification model capable of accurately predicting cardiovascular disease using the cardio_cleaned_week2.csv dataset.
Goal
Systematically explore algorithms to maximize predictive performance and identify the most promising candidates.
Outcome
Successfully deployed a detailed pipeline with ~73.6% cross-validation accuracy.