Explainability of random survival forests in predicting conversion risk from mild cognitive impairment to Alzheimer’s disease

Explainability of random survival forests in predicting conversion risk from mild cognitive impairment to Alzheimer’s disease

Abstract Random Survival Forests (RSF) has recently showed better performance than statistical survival methods as Cox proportional hazard (CPH) in predicting conversion risk from mild cognitive impairment (MCI) to Alzheimer’s disease (AD). However, RSF application in real-world clinical setting is...

Full description

Bibliographic Details
Main Authors: Alessia Sarica, Federica Aracri, Maria Giovanna Bianco, Fulvia Arcuri, Andrea Quattrone, Aldo Quattrone, for the Alzheimer’s Disease Neuroimaging Initiative
Format: Article
Language:English
Published: SpringerOpen 2023-11-01
Series:Brain Informatics
Subjects:
Survival analysis
Cox proportional hazard
Random Survival Forests
Machine learning
MCI conversion
AD progression
Online Access:https://doi.org/10.1186/s40708-023-00211-w

Similar Items

Similar Items