Articles published in this theme: 168 (scroll down to load remaining articles)
2026
Mental Health Needs of Families of Patients in Intensive Care Units and the Role of Mobile Health: Survey Study
JMIR Form Res 2026 (Mar 20); 10:e75461
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Impact of Tele-Intensive Care Units on the Clinical Outcomes of Critically Ill Patients With COVID-19: Retrospective Cohort Study
J Med Internet Res 2026 (Mar 19); 28:e64996
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Effectiveness of Virtual Reality–Based Early Rehabilitation Strategies on Pain, Sleep, Anxiety, Balance, Cognition, and Limb Motor Function in Adult Intensive Care Unit Patients: Systematic Review and Meta-Analysis of Randomized Controlled Trials
J Med Internet Res 2026 (Mar 06); 28:e81865
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Safety of Administration of Vasopressors Through Peripheral Compared to Central Venous Catheters in a Rural Kenyan Hospital: Protocol for a Prospective Observational Cohort Study
JMIR Res Protoc 2026 (Mar 05); 15:e81794
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The Effects of Digital Health Interventions for Family Members in Intensive Care Units: Systematic Review and Meta-Analysis of Randomized Controlled Trials
J Med Internet Res 2026 (Feb 25); 28:e83294
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Machine Learning Models for Mortality Prediction in Intensive Care Unit Patients With Ischemic Stroke Associated With Intracranial Artery Stenosis: Retrospective Cohort Study
JMIR Cardio 2026 (Feb 24); 10:e82042
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Patient Benefits in the Context of Sepsis-Related AI-Based Clinical Decision Support Systems: Scoping Review
J Med Internet Res 2026 (Jan 26); 28:e76772
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Evaluation of a Tablet-Based Emotion Regulation Intervention for Surrogate Decision-Makers of Patients With Critical Illness: Pilot Nonrandomized Trial
JMIR Form Res 2026 (Jan 19); 10:e73769
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2025
Large Language Models in Critical Care Medicine: Scoping Review
JMIR Med Inform 2025 (Nov 24); 13:e76326
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Association of Modifiable Lifestyle and Metabolic Factors With the Risk of Developing Sepsis: 2-Sample Mendelian Randomized Study
Interact J Med Res 2025 (Nov 03); 14:e72244
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Developing a Core Outcome Set and a Core Outcome Measurement Set for Studies Evaluating Interventions to Minimize Physical Restraint Use in Adult Intensive Care Units: Protocol for a Modified Delphi Study
JMIR Res Protoc 2025 (Nov 03); 14:e76405
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Effects, Feasibility, and Safety of an Early Mobilization Protocol With Immersive Virtual Reality for Dyspnea in Patients With Acutely Decompensated Heart Failure: The MOVE Randomized Clinical Trial
JMIR Form Res 2025 (Oct 31); 9:e80729
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Aggregating Patient Safety and Status Information in the Electronic Health Record to Support Time-Sensitive Mobility Interventions in the Intensive Care Unit: Protocol for the Design and Testing of a Clinical Decision Support Tool
JMIR Res Protoc 2025 (Oct 16); 14:e75752
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Harnessing the Power of Technology to Transform Delirium Severity Measurement in the Intensive Care Unit: Protocol for a Prospective Cohort Study
JMIR Res Protoc 2025 (Sep 25); 14:e62912
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Authors’ Reply to: Significant Risks and Responsibilities in the Clinical Use of AI Predictive Models. Comment on: “AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients”
J Med Internet Res 2025 (Sep 11); 27:e82112
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Significant Risks and Responsibilities in the Clinical Use of AI Predictive Models. Comment on: “AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients”
J Med Internet Res 2025 (Sep 11); 27:e81251
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Investigating Information Visualization to Combat Information Overload in Electronic Health Records: Protocol for a Randomized Controlled Trial
JMIR Res Protoc 2025 (Sep 09); 14:e74247
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AI Model Based on Diaphragm Ultrasound to Improve the Predictive Performance of Invasive Mechanical Ventilation Weaning: Prospective Cohort Study
JMIR Form Res 2025 (Sep 08); 9:e72482
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Predicting Episodes of Hypovigilance in Intensive Care Units Using Routine Physiological Parameters and Artificial Intelligence: Derivation Study
JMIR AI 2025 (Aug 27); 4:e60885
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Intensive Care Unit Patient Outcome Prediction Using ν-Support Vector Classification and Stochastic Signal Processing–Based Feature Extraction Techniques: Algorithm Development and Validation Study
JMIR AI 2025 (Aug 26); 4:e72671
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