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// Personal project
AlzheimInsight
I built a health screening tool that predicts Alzheimer's disease risk from a set of input assessments, using an ensemble of multiple machine learning models working together rather than relying on a single model.
Tech Stack
PythonMachine LearningEnsemble Modeling
How it works
Reliability mattered more here than anywhere else, so I didn't trust one model alone.
- Built an ensemble of multiple machine learning models working together on the same prediction.
- Used the ensemble approach specifically to make the prediction more reliable as an early-screening signal.
Why I built it
A single machine learning model can be confidently wrong, which is a real risk for a health-screening signal. I wanted a second and third opinion built into the system itself.
How I approached it
I trained multiple models on the same assessment data and combined their outputs into an ensemble, so the final risk prediction reflects agreement across models rather than one model's guess.
