Critical Care

Latest AI and machine learning research in critical care for healthcare professionals.

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Subcategories: Sepsis
Showing 2605-2625 of 5,099 articles
Integrating a host transcriptomic biomarker with a large language model for diagnosis of lower respiratory tract infection

Lower respiratory tract infections (LRTIs) are a leading cause of mortality worldwide and can be dif...

Artificial intelligence-enhanced Electrocardiography Score for Perioperative Risk Assessment in Non-cardiac Surgery

The role of electrocardiography (ECG) has been limited in the preoperative risk evaluation in noncar...

Retrospective Machine Learning Approach for Forecasting In-Hospital Death in ICU Patients After Cardiac Arrest

Accurate identification of patients at high risk of in-hospital mortality in intensive care units (I...

Beyond episodic early warning systems: a continuous clinical alert system for early detection of in-hospital deterioration

Efficient patient monitoring on the medical-surgical wards is crucial to prevent significant in-hosp...

Contextualized Biomedical Language Processing Enhances ICU Survival Prediction

Cerebrospinal fluid (CSF) culture is the diagnostic gold standard for neuroinfectious diseases such ...

Activation status of immune cells in the airway is a defining feature of severe fungal asthma

Airborne fungi are potent inducers of respiratory disease and cause the debilitating conditions seve...

Predicting ICU Readmission in Acute Pancreatitis Patients Using a Machine Learning-Based Model with Enhanced Clinical Interpretability

Acute pancreatitis (AP) is a common and potentially life-threatening gastrointestinal disease that p...

Artificial Intelligence Enabled Phenogrouping of Heart Failure with Preserved Ejection Fraction Depicts Early and End-Stage Trajectories

Heart failure with preserved ejection fraction is challenging to diagnose, precluding the initiation...

CLIF-Net: Intersection-guided Cross-view Fusion Network for Infection Detection from Cranial Ultrasound

This paper addresses the problem of detecting possible serious bacterial infection (pSBI) of infancy...

Case-Control Matching Erodes Feature Discriminability for AI-driven Sepsis Prediction in ICUs: A Retrospective Cohort Study

Sepsis remains a leading cause of intensive care unit (ICU) mortality worldwide, and early detection...

Development of a pilot machine learning model to predict successful cure in critically ill patients with community-acquired pneumonia

Severe community-acquired pneumonia (CAP) remains a major cause of critical illness, yet there are n...

Evaluating Few-Shot Prompting for Spectrogram-Based Lung Sound Classification Using a Multimodal Language Model

Traditional deep learning models for lung sound analysis require large, labeled datasets; multimodal...

CLINICAL VALIDATION OF SWAASA ARTIFICIAL INTELLIGENCE PLATFORM USING COUGH SOUNDS FOR SCREENING AND DIAGNOSIS OF RESPIRATORY DISEASES

Analysis of cough sounds have the potential to give a clue regarding the underlying respiratory dise...

Machine learning models to detect opioid misuse in Emergency Department patients at triage

Emergency department (ED) encounters represent valuable opportunities to initiate evidence-based tre...

Large Language Models Improve Coding Accuracy and Reimbursement in a Neonatal Intensive Care Unit

Diagnosis coding is essential for clinical care, research validity, and hospital reimbursement. In n...

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