A machine-learning system fordiabetes risk estimation.
DiabetesAI is an end-to-end machine-learning project that combines a trained classification model, a FastAPI backend, and a Next.js frontend.
Dataset
The model uses eight patient-level input variables and predicts the binary target column provided by the dataset.
Preprocessing
Some physiological fields contain zero values that are treated as missing measurements. The saved preprocessing pipeline handles missing values with median imputation and then standardizes the numeric features.
Model
The final candidate uses Gradient Boosting with hyperparameters selected through cross-validation and grid search on the training data.
Evaluation
The model was evaluated on a held-out test set after model selection. The classification threshold was selected using out-of-fold predictions from the training data.
From patient input to prediction.
This project is an educational machine-learning application. Its predictions are statistical model outputs and should not be interpreted as a medical diagnosis or as a substitute for professional medical advice.