AIMC Topic: Critical Care

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A Machine Learning Trauma Triage Model for Critical Care Transport.

JAMA network open
IMPORTANCE: Under austere prehospital conditions, rapid classification of injured patients for intervention or transport is essential for providing lifesaving care. Discerning which patients need care most urgently further allows for optimal allocati...

Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox.

Nutrients
BACKGROUND: Classification trees (CTs) are widely used machine learning algorithms with growing applications in clinical research, especially for risk stratification. Their ability to generate interpretable decision rules makes them attractive to hea...

Predicting infections with multidrug-resistant organisms (MDROs) in neurocritical care patients with hospital-acquired pneumonia (HAP): development of a novel multivariate prediction model.

Microbiology spectrum
Hospital-acquired pneumonia (HAP) is prevalent in the neuro-intensive care unit (NICU), significantly increasing susceptibility to infections with multidrug-resistant organisms (MDROs), which result in high mortality rates and substantial healthcare ...

Revolutionizing Intensive Care Unit Care: A Scoping Review of Multimodal Family Engagement Technologies.

Critical care nursing clinics of North America
This scoping review systematically examines the emerging field of multimodal family engagement technologies in intensive care units (ICUs). Despite significant advancements in medical technology, family engagement remains an underutilized resource in...

Clinicians' Perceptions and Potential Applications of Robotics for Task Automation in Critical Care: Qualitative Study.

Journal of medical Internet research
BACKGROUND: Interest in integrating robotics within intensive care units (ICUs) has been propelled by technological advancements, workforce challenges, and heightened clinical demands, including during the COVID-19 pandemic. The integration of roboti...

The future of artificial intelligence in cardiovascular monitoring.

Current opinion in critical care
PURPOSE OF REVIEW: Cardiovascular monitoring is essential for managing hemodynamic instability and preventing complications in critically ill patients. Conventional monitoring approaches are limited by predefined thresholds, dependence on clinician e...

Artificial Intelligence-Guided Bronchoscopy is Superior to Human Expert Instruction for the Performance of Critical-Care Physicians: A Randomized Controlled Trial.

Critical care medicine
OBJECTIVES: Bronchoscopy in the mechanically ventilated patient is an important skill for critical-care physicians. However, training opportunity is heterogenous and limited by infrequent caseload or inadequate instructor feedback for satisfactory co...

Prioritisation of functional needs for ICU intelligent robots in China: a consensus study based on the national survey and nominal group technique.

BMJ open
OBJECTIVE: This study aims to define the prioritisation of the needs for an intelligent robot's functions in the intensive care unit (ICU) from a clinical perspective.

Tailoring ventilation and respiratory management in pediatric critical care: optimizing care with precision medicine.

Current opinion in pediatrics
PURPOSE OF REVIEW: Critically ill children admitted to the intensive care unit frequently need respiratory care to support the lung function. Mechanical ventilation is a complex field with multiples parameters to set. The development of precision med...