"An explainable artificial intelligence framework for weaning outcomes ..."

Pu Wang et al. (2025)

> Home

Details and statistics

DOI: 10.1016/J.CMPB.2025.108811

access: closed

type: Journal Article

metadata version: 2025-06-11

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/cmpb/WangCCHDLHFZ25
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/cmpb/WangCCHDLHFZ25
Pu Wang, Teng-Hui Chen, Mei-Yun Chang, Hai-Yen Hsia, Meng Dai, Yifan Liu, Yeong-Long Hsu, Feng Fu, Zhanqi Zhao:
An explainable artificial intelligence framework for weaning outcomes prediction using features from electrical impedance tomography. Comput. Methods Programs Biomed. 267: 108811 (2025)

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.