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

Decision Support for Health Professionals (1551) Human Factors and Usability Case Studies (1008) Computer-Aided Diagnosis (253) Machine Learning (2087) Clinical Information and Decision Making (1930) Intensive Care Unit (ICU) (160) Nephrology/Renal Disorders (99)

Published on in Vol 13 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/63709, first published .
Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study

Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study

Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study

Authors of this article:

Benjamin Popoff1, 2 Author Orcid Image ;   Sandie Cabon2 Author Orcid Image ;   Marc Cuggia2 Author Orcid Image ;   Guillaume Bouzillé2 Author Orcid Image ;   Thomas Clavier1, 3 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Abdelbaky A, Elmasry W, Awad A, Khan S. Role of Artificial Intelligence in Critical Care Medicine: A Literature Review. Cureus 2025 View
  2. Havelikar U, Bembde A, Patil D, Shinde A, Sharma R, Patel V, Chaudhari N. Recent approaches of artificial intelligence in intensive care unit: A review. Intelligent Hospital 2025:100030 View
  3. Popoff B, Delange B, Nicolas J, Le Gall A, Dahamna B, Cuggia M, Clavier T, Bouzillé G. Development and validation of an interpretable predictive machine learning model for successful weaning of continuous renal replacement therapy. Scientific Reports 2025;15(1) View