An investigation into the impact of temporality on COVID-19 infection and mortality predictions: new perspective based on Shapley Values

An investigation into the impact of temporality on COVID-19 infection and mortality predictions: new perspective based on Shapley Values

Abstract Introduction Machine learning models have been employed to predict COVID-19 infections and mortality, but many models were built on training and testing sets from different periods. The purpose of this study is to investigate the impact of temporality, i.e., the temporal gap between trainin...

Full description

Saved in:
Bibliographic Details
Main Authors: Mingming Chen, Qihang Qian, Xiang Pan, Tenglong Li
Format: Article
Language:English
Published: BMC 2025-04-01
Series:BMC Medical Research Methodology
Subjects:
Temporality import
Shapley values
Random forest
COVID-19 infection prediction
COVID-19 mortality prediction
Online Access:https://doi.org/10.1186/s12874-025-02572-8
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s12874-025-02572-8

Similar Items