AI Medical Compendium Topic

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Intensive Care Units

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The Effects of Daytime Variation on Short-term Outcomes of Patients Undergoing Off-Pump Coronary Artery Bypass Grafting.

Journal of cardiothoracic and vascular anesthesia
OBJECTIVE: To evaluate the effects of time of surgery on the short-term outcomes of patients undergoing off-pump coronary artery bypass grafting (OPCABG).

Enhancing Pressure Injury Surveillance Using Natural Language Processing.

Journal of patient safety
OBJECTIVE: This study assessed the feasibility of nursing handoff notes to identify underreported hospital-acquired pressure injury (HAPI) events.

Attitudes on Artificial Intelligence use in Pediatric Care From Parents of Hospitalized Children.

The Journal of surgical research
INTRODUCTION: Artificial intelligence (AI) may benefit pediatric healthcare, but it also raises ethical and pragmatic questions. Parental support is important for the advancement of AI in pediatric medicine. However, there is little literature descri...

Machine learning vs. traditional regression analysis for fluid overload prediction in the ICU.

Scientific reports
Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine learning (ML) approaches may offer advantages over traditional regression techniques to predict it. ...

Natural language processing diagnosed behavioural disturbance phenotypes in the intensive care unit: characteristics, prevalence, trajectory, treatment, and outcomes.

Critical care (London, England)
BACKGROUND: Natural language processing (NLP) may help evaluate the characteristics, prevalence, trajectory, treatment, and outcomes of behavioural disturbance phenotypes in critically ill patients.

A deep learning approach for inpatient length of stay and mortality prediction.

Journal of biomedical informatics
PURPOSE: Accurate prediction of the Length of Stay (LoS) and mortality in the Intensive Care Unit (ICU) is crucial for effective hospital management, and it can assist clinicians for real-time demand capacity (RTDC) administration, thereby improving ...

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...

An interpretable ensemble learning model facilitates early risk stratification of ischemic stroke in intensive care unit: Development and external validation of ICU-ISPM.

Computers in biology and medicine
Ischemic stroke (IS) is a common and severe condition that requires intensive care unit (ICU) admission, with high mortality and variable prognosis. Accurate and reliable predictive tools that enable early risk stratification can facilitate intervent...