This paper is in the following e-collection/theme issue:

Precision Medicine (159) Intensive Care Unit (ICU) (160) Machine Learning (2076) Advanced Data Analytics in eHealth (209) Clinical Communication, Electronic Consultation and Telehealth (758) AI Language Models in Health Care (202) Decision Support for Health Professionals (1539)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/70118, first published .
Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study

Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study

Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study

Authors of this article:

Jing Wang1 Author Orcid Image ;   Qixiu Li1 Author Orcid Image ;   Can Xie2 Author Orcid Image ;   Xiaofei Li1 Author Orcid Image ;   Huikao Wang1 Author Orcid Image ;   Wei Xu2 Author Orcid Image ;   Ruyan Lv1 Author Orcid Image ;   Xiaobing Zhai2 Author Orcid Image ;   Ping Xu3 Author Orcid Image ;   Kefeng Li2 Author Orcid Image ;   Xi-Cheng Song4 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Tian Y, Zhuang Z, Su M, Yao X, Wang X, Li G. Predictive value of seven scoring systems for 28-day mortality in ICU patients with Sleep apnea–hypopnea syndrome (SAHS) and clinical indicators. European Journal of Medical Research 2025;30(1) View
  2. Grønbæk K, Mølgaard J, Sørensen K, Sigvardt E, Elvekjær M, Aasvang E, Meyhoff C. Risk factors for vital sign deviations in acutely admitted medical patients – an exploratory analysis. Hospital Practice 2025;53(1) View