Case study / Project archive
Heart Disease Prediction Dashboard
An educational dataset exploration and classifier-comparison dashboard.
Historical team prototype; individual contribution is not independently established. AI-assisted portfolio development.
The idea
The problem
Learn classifier comparison by putting dataset exploration, a consistent train/test split, and multiple model reports in one educational dashboard.
The implementation
What I built
The source brings exploratory charts, a reproducible split, classifier comparison, and prediction controls into one dashboard. The README lists a student team; individual implementation responsibility has not been independently established.
- Python
- Streamlit
- scikit-learn
Features
- Explore a tabular heart-disease dataset with distributions, correlations, and feature comparisons.
- Compare K-nearest neighbors, logistic regression, and Gaussian Naive Bayes on one held-out split.
- Inspect confusion matrices, classification reports, and input-based model predictions.
Architecture
- A single Streamlit application loads heart.csv and caches its training/data-preparation function.
- An 80/20 split precedes StandardScaler fitting on training data; the three scikit-learn estimators share transformed held-out inputs for comparison.
Engineering decisions
- Fit scaling on the training partition and use the same held-out partition across the compared classifiers.
Validation and measured results
- Source reviewed on 15 October 2026. The application and its external integrations were not executed in this review.
- Inspected load_and_train, the three classifier definitions, prediction paths, and report calculations. Model scores were not rerun or presented as clinical evidence.
Limits and unfinished work
- One dataset split does not establish clinical validity, calibration, generalization, or diagnostic safety.
- Older source can contain superseded descriptions. Numerical impact, adoption, awards, and deployment claims are not carried into this entry.
Evidence and sources
- Reviewed source and implementation
Public README and selected implementation files; source inspection only, without a reproduced runtime or benchmark. Inspected files: heart_dashboard.py.