A multimodal embedding model for sepsis data representation - Quiz - MDSpire

A multimodal embedding model for sepsis data representation

  • By

  • Tuo Liu

  • Yonglin Li

  • Hongyi Chen

  • Naiqing Li

  • Yan Zhang

  • Xuanqi Huang

  • Jin Wang

  • Rui Chen

  • Yuping Zeng

  • Yuntao Liu

  • Danwen Zheng

  • Darong Wu

  • Changdong Wang

  • Tao Yu

  • Xiaotu Xi

  • Zhongde Zhang

  • February 23, 2026

  • 0 min

Share

Original Source(s)

A multimodal embedding model for sepsis data representation

  • by Tuo Liu, Yonglin Li, Hongyi Chen, Naiqing Li, Yan Zhang, Xuanqi Huang, Jin Wang, Rui Chen, Yuping Zeng, Yuntao Liu, Danwen Zheng, Darong Wu, Changdong Wang, Tao Yu, Xiaotu Xi, Zhongde Zhang

  • February 23, 2026

Related Content

Immunometabolic reprogramming and glycolysis-associated signatures in sepsis: insights from single-cell RNA sequencing and machine learning

Elevated plasma cholesterol improves sepsis outcome by promoting hepatic metabolic reprogramming

FDA Clears AI Sepsis Warning System

An FDA-cleared AI tool developed at Johns Hopkins detects sepsis up to 48 hours earlier than clinicians — and has cut related deaths by 18%.