Critical Care

A novel hybrid sensor array with enhanced sensitivity and selectivity for biomarker detection of multiple respiratory diseases.

Electronic nose is an emergent technique for noninvasive disease detection via breath analysis, whic...

Pharmacoepidemiologic characterization of cannabis use and symptomatology in rheumatology using natural language processing of electronic health record clinic notes.

Up to 70% of patients with autoimmune rheumatic diseases (ARDs), including rheumatoid arthritis, pso...

Artificial Intelligence and Machine Learning in Health Care: Current Capabilities, Emerging Potential, and Future Directions.

This article reviews how artificial intelligence and machine learning are reshaping health care. Aft...

Wildfire-sourced PM2.5 and cause-specific emergency department visits in Victoria, Australia from 2014 to 2019.

Wildfires-sourced (WS) fine particulate matter (PM2.5) is known to adversely impact human health, wh...

Prediction of respiratory rate from schlieren images using artificial intelligence.

BACKGROUND AND OBJECTIVE: Respiratory rate is a fundamental physiological parameter and one of the e...

Machine Learning-Based Prediction of Postoperative Vasoplegia After Cardiac Surgery.

OBJECTIVE: To develop and internally validate a machine-learning model for the early prediction of p...

Pressure injury surveillance in the intensive care unit: Development, validation, and clinical application of a natural language processing algorithm.

INTRODUCTION: Pressure injuries (PIs) are one of the most common hospital-acquired complications in ...

Development and validation of deep continual learning model to sequentially learn multiple clinical prediction tasks for ICU patients.

BACKGROUND: ICU patients often suffer from critical and complex condition, and multiple potential ri...

Prospective Respiratory Motion Correction Using Machine Learning and Pilot Tone (PROMPT) in Cardiac MRI.

PURPOSE: To implement and evaluate the feasibility of a Pilot Tone (PT)-based prospective gating and...

Occupational Exposure to Welding Fumes Associated With Pulmonary Surfactant Lipid Compositional Changes, Inflammatory Activity, and Pulmonary Functioning.

OBJECTIVE: This study aimed to investigate alterations in the respiratory tract lining fluid phospho...

Artificial intelligence-guided nutritional therapy in the ICU.

PURPOSE OF REVIEW: Critical care nutrition remains a high-stakes and error-prone domain, particularl...

Development and validation of a machine learning model to predict 30-day mortality in ischemic stroke patients with consciousness impairment: Insights from MIMIC-IV database and multicenter ICU data in China.

BACKGROUND: Patients with ischemic stroke complicated by consciousness disorders remain associated w...

Extreme cardiac MRI analysis under respiratory motion: Results of the CMRxMotion challenge.

Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resona...

Learning curve for fenestrated-branched endovascular aortic repair using machine learning: A prospective national multicenter registry study.

OBJECTIVE: Fenestrated-branched endovascular aortic repair (F-BEVAR) is a complex procedure that req...

Authors reply: "How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a Behavioural Artificial Intelligence Technology (BAIT) approach".

The Ideal Human Care in Green ICU: An integrated AI framework for future ICU care - Letter on Arabfard et al.

An explainable machine learning model for comorbidity risk stratification in patients with fractures admitted to the intensive care unit: a multicenter study.

BACKGROUND: Among traumatic-fracture patients admitted to intensive care units (ICUs), those with su...

Artificial intelligence in nephrology: predicting CKD progression and personalizing treatment.

Chronic kidney disease (CKD) represents a major and expanding global health challenge, with prevalen...

Predicting Heart Failure From 12-Lead ECGs Using AI: A HeartShare/AMP-HF Pooled Cohort Analysis.

BACKGROUND: Artificial intelligence applied to electrocardiograms (ECG-AI) offers a scalable approac...

Responsible Use of Artificial Intelligence to Improve Kidney Care: A Statement from the American Society of Nephrology.

Artificial intelligence (AI) is rapidly transforming the delivery of kidney care through predictive ...

Letter to the editor: "How do experts classify sepsis cases for sepsis surveillance? Lessons learned from a behavioural artificial intelligence technology (BAIT) approach".

Behavioural Artificial Intelligence Technology (BAIT) has recently been proposed to codify expert re...