AIMC Topic: Critical Illness

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Construction and validation of a pain facial expressions dataset for critically ill children.

Scientific reports
Automatic pain assessment for non-communicative children is in high demand. However, the availability of related training datasets remains limited. This study focuses on creating a large-scale dataset of pain facial expressions specifically for Chine...

Enriching patient populations in ICU trials: reducing heterogeneity through machine learning.

Current opinion in critical care
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...

Relationship prediction between clinical subtypes and prognosis of critically ill patients with cirrhosis based on unsupervised learning methods: A study from two critical care databases.

International journal of medical informatics
BACKGROUND: Our objective was to identify distinct clinical subtypes among critically ill patients with cirrhosis and analyze the clinical features and prognosis of each subtype.

Timing of kidney replacement therapy in critically ill patients: A call to shift the paradigm in the era of artificial intelligence.

Science progress
Acute kidney injury (AKI) is a common condition in intensive care units (ICUs) and is associated with high mortality rates, particularly when kidney replacement therapy (KRT) becomes necessary. The optimal timing for initiating KRT remains a subject ...

Oxygen targets in critically ill patients: from pathophysiology to population enrichment strategies.

Medical gas research
Oxygen supplementation is widely used to enhance oxygen delivery and to treat or prevent hypoxia; however, it requires careful management to avoid the harmful effects of excessive oxygen exposure. Both hyperoxia (inspiratory oxygen fraction exceeding...

A machine learning model to predict intradialytic hypotension in pediatric continuous kidney replacement therapy.

Pediatric nephrology (Berlin, Germany)
BACKGROUND: Intradialytic hypotension (IDH) is associated with mortality in adults undergoing intermittent hemodialysis, but this relationship is unclear in critically ill children receiving continuous kidney replacement therapy (CKRT). We aim to eva...

Interpretable machine learning model for early prediction of disseminated intravascular coagulation in critically ill children.

Scientific reports
Disseminated intravascular coagulation (DIC) is a thrombo-hemorrhagic disorder that can be life-threatening in critically ill children, and the quest for an accurate and efficient method for early DIC prediction is of paramount importance. Candidate ...

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...

Predicting intra-abdominal hypertension using anthropometric measurements and machine learning.

Scientific reports
Almost one in four critically ill patients suffer from intra-abdominal hypertension (IAH). Currently, the gold standard for measuring intra-abdominal pressure (IAP) is via the bladder. Measurement of IAP is important to identify IAH early and thus im...