AIMC Topic: Critical Care

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Real-time prediction of intensive care unit patient acuity and therapy requirements using state-space modelling.

Nature communications Aug 8, 2025
Intensive care unit (ICU) patients often experience rapid changes in clinical status, requiring timely identification of deterioration to guide life-sustaining interventions. Current artificial intelligence (AI) models for acuity assessment rely on m...
Hospital Mortality Patient Acuity Critical Care Humans Artificial Intelligence Intensive Care Units
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Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Critical care (London, England) Jul 8, 2025
Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opportunities for enhanced diagnostic precision and personalized patient management. However, its integration into ICU clinical practice presents significan...
Consensus Critical Care Humans Artificial Intelligence Intensive Care Units
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A systematic multimodal assessment of AI machine translation tools for enhancing access to critical care education internationally.

BMC medical education Jul 8, 2025
BACKGROUND: Language barriers pose a significant barrier to expanding access to critical care education worldwide. Machine translation (MT) offers significant promise to increase accessibility to critical care content, and has rapidly evolved using n...
Humans Internationality Translations Multilingualism Artificial Intelligence Language Critical Care Translating Communication Barriers
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The liver reconditioning in critical care medicine.

Current opinion in anaesthesiology Jun 24, 2025
PURPOSE OF REVIEW: Machine perfusion has emerged as a transformative alternative to static cold storage in liver transplantation, necessitating a comprehensive review of current evidence. This article examines recent advances in preservation techniqu...
Liver Critical Care Liver Transplantation Humans Organ Preservation Perfusion
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A Machine Learning Trauma Triage Model for Critical Care Transport.

JAMA network open Jun 2, 2025
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...
Humans Machine Learning Retrospective Studies Middle Aged Emergency Medical Services Female Triage Adult Male Transportation of Patients Critical Care Wounds and Injuries Pennsylvania
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Methodological Review of Classification Trees for Risk Stratification: An Application Example in the Obesity Paradox.

Nutrients May 31, 2025
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...
Obesity Paradox Obesity Decision Trees Critical Care Critical Illness Intensive Care Units Risk Assessment Humans Machine Learning Algorithms
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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 May 15, 2025
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 ...
Anti-Bacterial Agents Retrospective Studies Intensive Care Units Female Aged Adult Humans Machine Learning ROC Curve Critical Care Logistic Models Cross Infection Nomograms Male Healthcare-Associated Pneumonia Middle Aged Drug Resistance, Multiple, Bacterial
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Enriching patient populations in ICU trials: reducing heterogeneity through machine learning.

Current opinion in critical care May 2, 2025
PURPOSE OF REVIEW: Despite the pivotal role of randomized controlled trials (RCTs) in critical care research, many have failed to demonstrate significant benefits, particularly in nutrition interventions. This review highlights how patient heterogene...
Randomized Controlled Trials as Topic Patient Selection Critical Care Precision Medicine Critical Illness Intensive Care Units Humans Artificial Intelligence Machine Learning Research Design
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Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study.

JMIR medical informatics Apr 23, 2025
BACKGROUND: Critically ill patients in intensive care units (ICUs) require continuous monitoring, generating vast amounts of data. Clinical decision support systems (CDSS) leveraging artificial intelligence (AI) technologies have shown promise in imp...
Attitude of Health Personnel Decision Support Systems, Clinical Critical Care Female Prospective Studies Male Adult Continuous Renal Replacement Therapy Middle Aged Cross-Sectional Studies Intensive Care Units Surveys and Questionnaires Humans Artificial Intelligence Physicians
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Use of Artificial Intelligence and Machine Learning in Critical Care Ultrasound.

Critical care clinics Apr 7, 2025
This article explores the transformative potential of artificial intelligence (AI) in critical care ultrasound AI technologies, notably deep learning and convolutional neural networks, now assisting in image acquisition, interpretation, and quality a...
Humans Artificial Intelligence Machine Learning Ultrasonography Critical Care
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