An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage

An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage

Abstract Spontaneous Intracerebral Hemorrhage (SICH) is a critical condition with high mortality rates, requiring prompt and effective prognostic assessment. This study aims to improve SICH outcome prediction by developing the Alpha Evolution Moss Growth Optimization (AEMGO) algorithm for feature se...

Full description

Saved in:
Bibliographic Details
Main Authors: Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu
Format: Article
Language:English
Published: SpringerOpen 2025-05-01
Series:Journal of Big Data
Subjects:
Spontaneous intracerebral hemorrhage
Radiomics
Feature selection
Moss growth optimization
Online Access:https://doi.org/10.1186/s40537-025-01175-w
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1186/s40537-025-01175-w

Similar Items