ClinivarResearch-Grade Disease Prediction
Predict diabetes outcomes with every model's verdict side-by-side
Built for diabetes clinical data. Input patient features and get instant ensemble results. Then compare how Logistic Regression, Random Forest, XGBoost, SVM, and Neural Network each arrive at their verdict — transparent, not black-box. More conditions coming.
A research-grade prediction ensemble spanning logistic regression to neural networks
The Prediction Pipeline
From clinical input to ensemble output — transparent comparison at every step.
Select Disease
Choose from supported conditions. Each disease has its own set of clinical features and trained models.
Enter Features
Input clinical measurements through a form designed for each condition's diagnostic criteria.
Compare Results
See every model's prediction side-by-side with confidence metrics, feature importance, and ensemble consensus.
Available Models
Each disease is evaluated across multiple algorithms. Top performer highlighted below.