Critical Care

Bioinformatics analysis reveals the association of bile acid metabolism-related genes with sepsis.

BACKGROUND: Sepsis, is a life-threatening syndrome triggered by infection. Bile acid metabolism may be involved in the pathogenesis of sepsis, the underlying association has not yet been elucidated. Thus, we aimed to screen for bile acid metabolism-related biomarkers of sepsis and discover the potential association. METHODS: Sepsis-related datasets were downloaded from the Gene Expression Omnibus ...

Study on the construction and verification of intraoperative pressure injury risk prediction model for children undergoing cardiac surgery.

BACKGROUND: This study applied nomogram to develop an intraoperative acquired pressure injury (IAPI) risk prediction model for pediatric cardiac surgery patients, validated its predictive performance, and aims to provide evidence-based guidance for IAPI prevention in pediatric cardiac surgery. METHODS: A retrospective analysis of clinical surgical data from 1,179 pediatric patients undergoing card...

Machine learning approach to analyzing complex care coordination patterns for medically complex children.

BACKGROUND: The number of children with medical complexity (CMC) in Japan has exceeded 20,000, doubling over the past 15 years, forming a significant ...

LWF-YOLO: a lightweight framework based YOLO for blood cell detection.

Accurate detection of blood cells-red blood cells, white blood cells, and platelets-is essential for diagnosing hematological disorders such as anemia...

Machine learning models predicting extubation success in mechanically ventilated patients: a systematic review and meta-analysis.

BACKGROUND: Optimal timing of extubation in mechanically ventilated patients remains a major challenge in intensive care. Machine learning (ML) models...

Correction: Enterocutaneous Fistula-Associated Sepsis and Mortality: Development and Validation of a Multimodal Artificial Intelligence Prediction Model.

[This corrects the article DOI: 10.2196/79985.].

Deep Learning-Enabled Robust Regional Lung Function Assessment in Mechanically Ventilated AECOPD Patients Using EIT Parameters.

Reliable quantification of regional lung function via electrical impedance tomography (EIT) in mechanically ventilated AECOPD patients requires identi...

ASTHMA AT THE CROSSROADS: FROM ANTI-TNF-α SETBACKS TO NEXT-GENERATION BIOLOGICS TARGETING TYPE 1 AND TYPE 2 INFLAMMATION.

Severe asthma remains a major unmet clinical challenge due to its marked immunological heterogeneity and the limited efficacy of current therapies in ...

Transformer-based classification with enhanced causal explainability from otoscopic images.

Otitis media is a major cause of hearing loss, particularly in children. However, nonspecific symptoms and subjective evaluations make its diagnosis c...

Fostering trust in digital respiratory medicine: the open access ERS CONNECT digital health technology repository.

Access to digital health tools is rapidly expanding, but adoption in respiratory care remains fragmented. The ERS CONNECT Repository provides a truste...

A Multitask Learning framework for E-commerce time series analytics: Operational risk, demand forecasting, and anomaly detection.

The study presents MT-PyraRisk, a multi-task learning framework that integrates pyramidal attention mechanisms for cross-border e-commerce risk predic...

Development and validation of a novel multimodal deep neural network model based on CBC digit parameters and scattergrams for rapid hematolymphoid malignancy classification: a multicenter cohort study.

BACKGROUND: Rapid screening of hematolymphoid malignancies (HMs) by complete blood cell count (CBC) is crucial for choosing the next appropriate worku...

Cardio-respiratory deep learning model to predict hospital admission from emergency department electrocardiogram images and respiration videos: a prospective study.

BACKGROUND: Early prediction of hospital admission at the emergency department (ED) triage can improve patient flow and resource allocation. Most exis...

Reporting follow-up budgets for diagnostic and predictive AI.

OBJECTIVE: To argue that diagnostic and predictive AI should be evaluated by both classification performance and the downstream work their outputs cre...

Transformer-Based Deep Learning Model for Predicting Hemoglobin Response to Mircera® in Hemodialysis Patients.

BACKGROUND: Anemia management in hemodialysis (HD) depends on individualized erythropoiesis-stimulating agent (ESA) dosing to achieve and maintain tar...

Impact of an Artificial Intelligence-Powered Clinical Decision Support System for Acute Kidney Injury Prevention in the Intensive Care Unit: Single-Center Uncontrolled Before-and-After Implementation Study.

BACKGROUND: Acute kidney injury (AKI) is a frequent and serious complication among hospitalized patients, particularly in critical care settings, wher...

The hidden infectious disease-related sepsis risk of wildfire-specific PM2.5.

Wildfire smoke is a major source of fine particulate matter (PM2.5) and may increase vulnerability to severe infectious outcomes such as sepsis, a con...

Prediction of incident atrial fibrillation from retinal fundus images using a multimodal foundation model.

Atrial fibrillation (AF), a common cardiac arrhythmia, presents significant challenges for early detection and management due to its asymptomatic and ...

Integrated transcriptomic and experimental validation reveal that N‑acetylcysteine ameliorates acute liver failure through multi‑target synergistic regulation of pyroptosis and related signaling networks.

Pyroptosis is a major contributor to the pathophysiology of acute liver failure (ALF), a condition with high mortality. Although N‑acetylcysteine (NAC...

Explainable machine learning for the early differentiation of pediatric bronchopneumonia using routine laboratory parameters.

OBJECTIVE: Early differentiation of pediatric acute respiratory infections in outpatient and emergency settings is often hindered by nonspecific clini...