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All ICU nursing staff were eligible to participate in this study. Nursing staff were the primary users and facilitators of the ICU Family Link system. The system was mainly used for web-based bedside visits, rather than formal medical updates from the ICU medical team, although it was available if needed. The survey was open to any ICU staff member. Staff were recruited via emails, verbal reminders at nursing handover, and paper copies of surveys left in break rooms and main staff areas.
JMIR Hum Factors 2025;12:e54560
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Large Language Model–Based Critical Care Big Data Deployment and Extraction: Descriptive Analysis
ICU-GPT does not develop new LLM models but utilizes and is compatible with all Open AI application programming interface (API) models. We chose Open AI API-compatible models for ICU-GPT development for several reasons. First, our research team is more familiar with Open AI. There is also a large number of models compatible with the Open AI API, including GPT-3.5, GPT-4o, and GPT-4o mini, offering wide applications and cost-effectiveness.
JMIR Med Inform 2025;13:e63216
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This intricate physiological course of muscle events and interactions may become disturbed in patients treated in the intensive care unit (ICU). Swallowing impairment or dysphagia is not uncommon in ICU patients with a reported prevalence of up to 62% of those who were recently extubated [3].
JMIR Serious Games 2025;13:e60685
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Although individual vital signs (eg, heart rate, blood pressure) are easily accessible through continuous bedside monitoring, they are not valid for ICU pain assessment due to inconsistent findings across studies and clinically insignificant variation in their values (
Although the validity of the NOL is supported in anesthesia, its use in the ICU is new. To our knowledge, we are the first research team to have pilot-tested the use of the NOL for nociception and pain assessment in the ICU.
JMIR Res Protoc 2025;14:e60672
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Agitation can lead to the accidental removal of tubes and catheters, compromising patient safety, extending ICU stays, and causing complications [5]. Throughout the treatment period, nurses must regularly evaluate the levels of agitation and sedation and titrate the dosages of sedatives accordingly for patient care.
Various scales have been developed for measuring sedation effects. Among them, the Richmond Agitation-Sedation Scale (RASS) is the most reliable and effective [6].
JMIR Med Inform 2025;13:e63601
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The participants were randomly assigned to the intervention and control groups in a 1:1 ratio at the time of admission to the ICU. The randomization sequence was generated by the staff. No blinding was applied during the study period. Anthropometric and clinical data were collected from the patients’ self-reporting or the electronic medical records at baseline and at the end of their ICU stay or death after the intervention.
J Med Internet Res 2025;27:e67012
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To understand how clinicians approach and reason about the data annotation process, we conducted an experimental study that involved members of the clinical staff from the ICU manually annotating excerpts of time-series data printed on paper. Observations taken during task completion served as a basis for analysis and were used to derive the requirements for the data annotation software.
JMIR Hum Factors 2025;12:e56880
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Within the intensive care unit (ICU), ECMO is one of the most complicated therapies, requiring not only extensive knowledge of cardiopulmonary physiology and expertise with intricate circuit components but also skills to rapidly respond to emergent situations [2]. Therefore, high-fidelity simulation trainings are critical to practice skills and work through different emergency scenarios, such as the blood pump falling from the drive unit [3].
JMIR Med Educ 2025;11:e57424
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Our study of the sociotechnical integration of AI centers around critical care teams, specifically intensive care unit (ICU) nurses and physicians. The ICU context was selected due to the particularly high job demands and increased rates of burnout, which were exacerbated by the extreme work conditions during the SARS-Co V-2 pandemic [35-37].
J Med Internet Res 2025;27:e50852
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