Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study

Abstract This study aimed to develop an interpretable machine learning model to predict methylene blue (MB) responsiveness in adult patients with refractory septic shock and to identify key factors influencing MB responsiveness using the SHapley Additive exPlanations (SHAP) approach. We retrospectiv...

Full description

Saved in:
Bibliographic Details
Main Authors: Shasha Xue, Li Li, Zhuolun Liu, Feng Lyu, Fan Wu, Panxiao Shi, Yongmin Zhang, Lina Zhang, Zhaoxin Qian
Format: Article
Language:English
Published: Nature Portfolio 2025-03-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-025-89934-w
Tags: Add Tag
No Tags, Be the first to tag this record!