Critical Care

Prospective genomic and epidemiologic surveillance of Klebsiella pneumoniae in a tertiary NICU.

BACKGROUND: Klebsiella pneumoniae complex (Kp) is a relevant neonatal pathogen colonizing preterm in...

Artificial intelligence and computerized decision support in adult intensive care: A systematic review of randomized controlled trials.

BACKGROUND: Artificial intelligence (AI) and computerized clinical decision support systems (CDSS) a...

Identification and multi-layered experimental validation of feature genes related to butyrate metabolism and oxidative stress in sepsis.

The mechanisms underlying sepsis remain poorly understood and specific therapeutic options remain la...

External Validation of the PIPRA Model for Postoperative Delirium Prediction in a Japanese ICU Cohort: Integrating AI-Based Risk Assessment into Perioperative Care.

BACKGROUND: Postoperative delirium (POD) is a prevalent and serious complication in older surgical p...

Prediction of the respiratory disease incidence based on environmental factors using machine learning techniques in Penang, Malaysia.

Traditional statistical models often struggle to accurately predict global burden of respiratory dis...

Automated estimation of drain output in postoperative patients using deep learning on clinical images.

Postoperative drains are essential components of care in general surgery and intensive care units, w...

Development and validation of a machine learning model for predicting positive blood cultures using vital signs in ICU patients.

Bloodstream infections require timely and appropriate diagnosis and treatment, as inadequate managem...

Association between platelet-albumin-bilirubin score and 30-day in-hospital mortality in patients with sepsis: evidence from a large database and machine learning modeling.

Emerging technologies and AI-assisted tools in cardiopulmonary monitoring.

PURPOSE OF REVIEW: Cardiopulmonary monitoring is fundamental to critical care, yet traditional appro...

Explainable machine learning integrating bioelectrical impedance for 6-month cardiovascular risk in peritoneal dialysis.

Peritoneal dialysis (PD) is a common treatment for end-stage renal disease, yet cardiovascular disea...

A multi-scale patch transformer for cross-sequence forecasting: Application to EMG-respiration prediction.

Accurately predicting respiratory signals from electromyography envelopes is crucial for non-invasiv...

Lightweight large language models for early sepsis prediction via a semantic abstraction rule engine.

Sepsis remains a major global health challenge due to its high mortality rate and the difficulty of ...

LSTM-GRU hybrid model for multi-layer microclimate prediction in solar greenhouse.

Precise microclimate control across vertical canopy layers is critical for optimizing crop productio...

Key factors of the deranged antiviral response in elderly patients with COVID-19: a machine-learning analysis.

Age is a well-known risk factor to develop severe viral respiratory infections, including severe COV...

Explainable machine learning using urinary metabolomics to predict pediatric sepsis-associated acute kidney injury: a two-center prospective observational study.

Sepsis-induced acute kidney injury (S-AKI) is a common and serious complication in critically ill ch...

Physiological predictors of respiratory motor plasticity: A machine-learning reappraisal of phrenic motor facilitation.

Acute intermittent hypoxia (AIH)-induced phrenic long-term facilitation (pLTF) is a well-established...

Enhancing large language model clinical support information with machine learning risk and explainability: a feasibility study.

BACKGROUND: Current machine learning (ML) prediction models offer limited guidance for individualize...

Artificial intelligence-based prediction of radio-cephalic arteriovenous fistula maturation using preoperative duplex examination: a retrospective multicenter cohort study.

Establishing a functional arteriovenous fistula (AVF) is crucial to ensure effective dialysis treatm...

Rhythms of mood: Bidirectional regulation of molecular clocks and neurotransmission in affective disorders.

Mood disorders, primarily major depressive and bipolar disorder, are characterized by significant ne...

Development of a calibrated logistic regression clinical risk score for predicting postoperative sepsis following retrograde intrarenal surgery.

Effective elimination of respiratory misregistration-induced attenuation correction errors in PET/CT via deep learning trained on data-driven gated PET from strictly respiratory-phase-matched PET/CT cases.