Critical Care

MOAL: Multi-view Out-of-distribution Awareness Learning.

Multi-view learning integrates data from multiple sources to enhance task performance by improving data quality. However, existing approaches primarily focus on intra-distribution data learning and consequently fail to identify out-of-distribution instances effectively. This paper introduces a method to improve the perception of out-of-distribution data in multi-view situations. First, we employ m...

Quantitative computed tomography imaging classification of cement dust-exposed patients-based Kolmogorov-Arnold networks.

BACKGROUND: Occupational health assessment is critical for detecting respiratory issues caused by harmful exposures, such as cement dust. Quantitative computed tomography (QCT) imaging provides detailed insights into lung structure and function, enhancing the diagnosis of lung diseases. However, its high dimensionality poses challenges for traditional machine learning methods.

Novel machine learning models for the prediction of acute respiratory distress syndrome after liver transplantation.

Early prediction of acute respiratory distress syndrome (ARDS) after liver transplantation (LT) facilitates timely intervention. We aimed to develop a...

The extent of Skeletal muscle wasting in prolonged critical illness and its association with survival: insights from a retrospective single-center study.

OBJECTIVE: Muscle wasting in critically ill patients, particularly those with prolonged hospitalization, poses a significant challenge to recovery and...

Development and validation of a machine learning model for real-time prediction of invasive mechanical ventilation weaning readiness.

PURPOSE: To develop and validate a bedside machine learning (ML) decision support tool for prediction of invasive mechanical ventilation (IMV) weaning...

Predicting Mortality in Atrial Fibrillation Patients Treated with Direct Oral Anticoagulants: A Machine Learning Study Based on the MIMIC-IV Database.

Atrial fibrillation (AF) is a common arrhythmia linked to increased mortality and significant healthcare burden, especially in the elderly. Direct Or...

Analysis of the heterogeneous treatment effect of vasoactive drug dosage and time on hospital mortality across different sepsis phenotypes: a retrospective cohort study.

BACKGROUND: The heterogeneity of sepsis poses challenges for the individualized treatment of vasoactive drugs.

MSFusion: A multi-source hybrid feature fusion network for accurate grading of invasive breast cancer using H&E-stained histopathological images.

Invasive breast cancer (IBC) is a prevalent malignant tumor in women, and precise grading plays a pivotal role in ensuring effective treatment and enh...

Association between fibrinogen levels and prognosis in critically bleeding patients: exploration of the optimal therapeutic threshold.

BACKGROUND: Severe bleeding is a leading cause of ICU admission and mortality. Fibrinogen plays a crucial role in prognosis, yet optimal thresholds an...

Artificial intelligence in the management of patient-ventilator asynchronies: A scoping review.

BACKGROUND: Patient-ventilator asynchronies (PVAs) are frequent complications in mechanically ventilated patients, contributing to adverse outcomes su...

Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders.

Obstructive sleep apnea (OSA) and related hypoxia are well-established cardiovascular and neurocognitive risk factors. Current multi-sensor diagnostic...

A demand-centered scheduling framework for shared supercomputing resources: modeling, metrics, and case insights.

The exponential growth of artificial intelligence and data-intensive applications has led to a significant surge in demand for supercomputing resource...

Influence of the CONCERN Early Warning System on Unanticipated ICU Transfers, In-Hospital Mortality, and Length of Stay: Results from a Multi-site Pragmatic Randomized Controlled Clinical Trial.

Communicating Narrative Concerns Entered by RNs Early Warning System (CONCERN EWS) is a machine-learning predictive model that leverages nursing surve...

Lung MRI: Indications, Capabilities, and Techniques- Expert Panel Narrative Review.

Lung MRI provides both structural and functional information across a spectrum of parenchymal and airway pathologies. MRI, using current widely availa...

Imbalanced feature generation based on bootstrap power spectral curve for estimating respiratory rate.

Rapid respiratory rate (RR) changes in older adults may indicate serious illness. Therefore, accurately estimating RR for cardiorespiratory fitness is...

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-hospital adverse events. Standard episodic inpatient a...

Construction and clinical visualization application of a predictive model for mortality risk in sepsis patients based on an improved machine learning model.

OBJECTIVE: To explore the construction and clinical visualization application of a mortality risk prediction model for sepsis patients based on an imp...

Early Prediction of Mortality Risk in Acute Respiratory Distress Syndrome: Systematic Review and Meta-Analysis.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a life-threatening condition associated with high mortality rates. Despite advancements in c...

Real-time respiratory motion forecasting with online learning of recurrent neural networks for accurate targeting in externally guided radiotherapy.

BACKGROUND AND OBJECTIVE: In lung radiotherapy, infrared cameras can track reflective objects on the chest to estimate tumor motion due to breathing. ...

Contemporary Prevention and Management of Postoperative Delirium in Cardiac Surgery Patients.

This review examines the prevention and management of postoperative delirium in cardiac surgery patients, a frequent complication linked with signific...