Clinical Reference Interval Estimation with Reference Interval Network (RINet)
Convert correlation to covariance matrix
Extract histogram features from standardized data
Internal function to load model and scaler
Internal function to load scaler
Predict statistics of the underlying reference distribution from 1D mi...
Predict statistics of the underlying reference distribution from 2D mi...
Predict statistics of the underlying reference distribution from mixtu...
RINet: Predict Clinical Reference Intervals from Mixture Distributions
Predicts statistics of a reference distribution from a mixture of raw clinical measurements (healthy and pathological). Uses pretrained CNN models to estimate the mean, standard deviation, and reference fraction from 1D or 2D sample data. Methods are described in LeBien, Velev, and Roche-Lima (2026) "RINet: synthetic data training for indirect estimation of clinical reference distributions" <doi:10.1016/j.jbi.2026.104980>.