AIMC Topic: Critical Care
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Machine learning prediction of unexpected readmission or death after discharge from intensive care: A retrospective cohort study.
Journal of clinical anesthesia
Oct 14, 2024
BACKGROUND: Intensive care units (ICUs) harbor the sickest patients with the utmost needs of medical care. Discharge from ICU needs to consider the reason for admission and stability after ICU care. Organ dysfunction or instability after ICU discharg...
Is artificial intelligence prepared for the 24-h shifts in the ICU?
Anaesthesia, critical care & pain medicine
Oct 3, 2024
Integrating machine learning (ML) into intensive care units (ICUs) can significantly enhance patient care and operational efficiency. ML algorithms can analyze vast amounts of data from electronic health records, physiological monitoring systems, and...
Development and validation of a sepsis risk index supporting early identification of ICU-acquired sepsis: an observational study.
Anaesthesia, critical care & pain medicine
Oct 2, 2024
BACKGROUND: Sepsis is a threat to global health, and domestically is the major cause of in-hospital mortality. Due to increases in inpatient morbidity and mortality resulting from sepsis, healthcare providers (HCPs) would accrue significant benefits ...
Machine Learning Based Prediction of Imminent ICP Insults During Neurocritical Care of Traumatic Brain Injury.
Neurocritical care
Sep 25, 2024
BACKGROUND: In neurointensive care, increased intracranial pressure (ICP) is a feared secondary brain insult in traumatic brain injury (TBI). A system that predicts ICP insults before they emerge may facilitate early optimization of the physiology, w...
Robotic Assisted Transcranial Doppler Monitoring in Acute Neurovascular Care: A Feasibility and Safety Study.
Neurocritical care
Sep 19, 2024
BACKGROUND: Transcranial color Doppler (TCD) is currently the only noninvasive bedside tool capable of providing real-time information on cerebral hemodynamics. However, being operator dependent, TCD monitoring is not feasible in many institutions. R...
Should AI models be explainable to clinicians?
Critical care (London, England)
Sep 12, 2024
In the high-stakes realm of critical care, where daily decisions are crucial and clear communication is paramount, comprehending the rationale behind Artificial Intelligence (AI)-driven decisions appears essential. While AI has the potential to impro...
Timely ICU Outcome Prediction Utilizing Stochastic Signal Analysis and Machine Learning Techniques with Readily Available Vital Sign Data.
IEEE journal of biomedical and health informatics
Sep 5, 2024
The ICU is a specialized hospital department that offers critical care to patients at high risk. The massive burden of ICU-requiring care requires accurate and timely ICU outcome predictions for alleviating the economic and healthcare burdens imposed...
Advances in critical care nephrology through artificial intelligence.
Current opinion in critical care
Aug 30, 2024
PURPOSE OF REVIEW: This review explores the transformative advancement, potential application, and impact of artificial intelligence (AI), particularly machine learning (ML) and large language models (LLMs), on critical care nephrology.
Generative AI in Critical Care Nephrology: Applications and Future Prospects.
Blood purification
Aug 30, 2024
BACKGROUND: Generative artificial intelligence (AI) is rapidly transforming various aspects of healthcare, including critical care nephrology. Large language models (LLMs), a key technology in generative AI, show promise in enhancing patient care, st...
AI-based derivation of atrial fibrillation phenotypes in the general and critical care populations.
EBioMedicine
Aug 16, 2024
BACKGROUND: Atrial fibrillation (AF) is the most common heart arrhythmia worldwide and is linked to a higher risk of mortality and morbidity. To predict AF and AF-related complications, clinical risk scores are commonly employed, but their predictive...
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