AIMC Topic: Critical Care

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Robot-assisted early mobilization for intensive care unit patients: Feasibility and first-time clinical use.

International journal of nursing studies
BACKGROUND: Early mobilization is only carried out to a limited extent in the intensive care unit. To address this issue, the robotic assistance system VEMOTION® was developed to facilitate (early) mobilization measures more easily. This paper descri...

Application of Machine Learning Techniques to Development of Emergency Medical Rapid Triage Prediction Models in Acute Care.

Computers, informatics, nursing : CIN
Given the critical and complex features of medical emergencies, it is essential to develop models that enable prompt and suitable clinical decision-making based on considerable information. Emergency nurses are responsible for categorizing and priori...

The Pediatric Data Science and Analytics Subgroup of the Pediatric Acute Lung Injury and Sepsis Investigators Network: Use of Supervised Machine Learning Applications in Pediatric Critical Care Medicine Research.

Pediatric critical care medicine : a journal of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies
OBJECTIVE: Perform a scoping review of supervised machine learning in pediatric critical care to identify published applications, methodologies, and implementation frequency to inform best practices for the development, validation, and reporting of p...

Finding the best trade-off between performance and interpretability in predicting hospital length of stay using structured and unstructured data.

PloS one
OBJECTIVE: This study aims to develop high-performing Machine Learning and Deep Learning models in predicting hospital length of stay (LOS) while enhancing interpretability. We compare performance and interpretability of models trained only on struct...

[The Swecrit Biobank, associated clinical registries, and machine learning (artificial intelligence) improve critical care knowledge].

Lakartidningen
The unique Swecrit Biobank and its associated clinical registries for sepsis, ARDS, cardiac arrest, trauma, and COVID-19 include more than 150,000 blood samples and descriptions of critically ill patients. These assets provide a unique opportunity to...

Continuous visualization and validation of pain in critically ill patients using artificial intelligence: a retrospective observational study.

Scientific reports
Machine learning tools have demonstrated viability in visualizing pain accurately using vital sign data; however, it remains uncertain whether incorporating individual patient baselines could enhance accuracy. This study aimed to investigate improvin...

Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings : A Simulation Study.

Annals of internal medicine
BACKGROUND: Substantial effort has been directed toward demonstrating uses of predictive models in health care. However, implementation of these models into clinical practice may influence patient outcomes, which in turn are captured in electronic he...

Mortality prediction using medical time series on TBI patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Traumatic Brain Injury (TBI) is one of the leading causes of injury-related mortality in the world, with severe cases reaching mortality rates of 30-40%. It is highly heterogeneous both in causes and consequences making more...

An interpretable deep learning model for time-series electronic health records: Case study of delirium prediction in critical care.

Artificial intelligence in medicine
Deep Learning (DL) models have received increasing attention in the clinical setting, particularly in intensive care units (ICU). In this context, the interpretability of the outcomes estimated by the DL models is an essential step towards increasing...

The future of artificial intelligence in clinical nutrition.

Current opinion in clinical nutrition and metabolic care
PURPOSE OF REVIEW: Artificial intelligence has reached the clinical nutrition field. To perform personalized medicine, numerous tools can be used. In this review, we describe how the physician can utilize the growing healthcare databases to develop d...