A novel hyperparameter search approach for accuracy and simplicity in disease prediction risk scoring.

ABSTRACT:

Objective

Develop a novel technique to identify an optimal number of regression units corresponding to a single risk point, while creating risk scoring systems from logistic regression-based disease predictive models. The optimal value of this hyperparameter balances simplicity and accuracy, yielding risk scores of small scale and high accuracy for patient risk stratification.

Materials and methods

The proposed technique applies an adapted line search across all potential hyperparameter values. Additionally, DeLong test is integrated to ensure the selected value produces an accuracy insignificantly different from the best achievable risk score accuracy. We assessed the approach through two case studies predicting diabetic retinopathy (DR) within six months and hip fracture r

SUBMITTER: Lu Y 

PROVIDER: S-EPMC11258418 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature