Critical Care

Paediatric respiratory sound classification by integrating local feature extraction and global context modeling.

BACKGROUND AND OBJECTIVE: Automated respiratory sound classification based on deep learning is critical for enhancing diagnostic precision and efficiency in respiratory disease. Research on respiratory sound classification for adults is extensive, whereas work on paediatric respiratory sounds is still scarce. Compared to adults, paediatric respiratory sounds typically contain more high-frequency c...

Classification of patient-ventilator asynchronies, development of an updated conceptual framework: Scoping review.

PURPOSE: Patient-ventilator asynchrony (PVA), a mismatch between a patient's respiratory effort and the ventilator's support, affects up to 85% of patients receiving invasive mechanical ventilation (IMV). It is associated with prolonged ventilation, increased complications, and higher mortality. Existing classification systems for PVA are inconsistent, difficult to apply in clinical settings, and ...

Implementing AI-enabled chest X-ray for community-based integrated screening for tuberculosis, chronic respiratory diseases, and cardiovascular diseases in Nigeria.

BACKGROUND: Low- and middle-income countries face a growing dual burden of communicable and non-communicable diseases, while services remain verticall...

AI-Enabled Wearable Ultrasound for Noninvasive Central Venous Pressure Monitoring.

Central venous pressure (CVP) is a key indicator of right ventricular preload, but measurement with a central venous catheter (CVC) is invasive, time-...

Explainable artificial intelligence in ICU admission prediction for methanol poisoning patients: a comparative study of deep and machine learning models.

BACKGROUND: Methanol poisoning poses significant challenges due to its rapid progression and high mortality rate, necessitating timely and accurate IC...

Development and external validation of a multimodal artificial intelligence mortality prediction model of critically ill patients using multicenter data.

BACKGROUND: Early prediction of in-hospital mortality in critically ill patients can aid clinicians in optimizing treatment. The objective was to deve...

EMBC Special Issue: SAM-HovNet: SAM-Enhanced Multi-Class Nucleus Segmentation and Classification in Hepatocellular Carcinoma Slides.

Hepatocellular carcinoma (HCC) is the most common primary liver cancer and a leading cause of cancer-related mortality. Manual nuclear analysis in HCC...

Enhancing pediatric cardiac auscultation with data-driven murmur detection: toward tele-consultation applications.

BACKGROUND: Pediatric cardiac tele-auscultation is often limited by poor signal quality due to respiratory sounds, motion artifacts, and environmental...

From Synthesis to Failure: In Situ Characterization of Lithium-Ion Battery Cathodes.

Developing high-performance, long-life lithium-ion batteries requires an in-depth understanding of cathode material synthesis, lithium-ion (de)interca...

Age-specific climate sensitivity of respiratory hospitalizations in a tropical coastal city: 20-year Random Forest forecasts.

Respiratory diseases remain a major public health challenge in tropical coastal cities, where persistent heat-humidity interactions and climate variab...

Practical Optimization of Deep Learning Models for Cuffless Blood Pressure Estimation From Photoplethysmography.

To improve deep learning-based cuffless blood pressure (BP) estimation from photoplethysmography (PPG) for continuous, non-invasive monitoring wh...

Validation of a deep learning-based system for sleep staging, arousal detection, and respiratory event scoring in atrial fibrillation patients.

PURPOSE: Obstructive sleep apnea is a common yet underdiagnosed sleep disorder in patients with atrial fibrillation (AF). Although polysomnography (PS...

Subphenotypes of pneumonia defined by pulmonary histopathological features.

RATIONALE: Establishing subphenotypes of pneumonia based on host biology will be a step toward using host-directed therapies (to complement microbe-di...

AI-quantified Myosteatosis at CAC CT for Prediction of Atrial Fibrillation and Heart Failure: The Multi-Ethnic Study of Atherosclerosis.

Purpose To evaluate whether the artificial intelligence (AI)-quantified mean thoracic skeletal muscle (TSM) attenuation from coronary artery calcium (...

Automated Differentiation of Oral Red-White Lesions: An Interpretable Deep Learning Approach Combining Ensemble Architectures and Saliency Maps.

INTRODUCTION: Oral Potentially Malignant Disorders (OPMDs), including Leukoplakia and Erythroplakia, carry significant risks of malignant transformati...

A projection-domain deep learning approach for respiratory motion correction of myocardial perfusion imaging using a multi-pinhole solid-state SPECT.

BACKGROUND: Myocardial perfusion imagining (MPI) is a nuclear medicine technique used in the assessment of coronary artery disease. Differences in the...

Predictive Modeling of the Need for Tracheostomy after Traumatic Cervical Spinal Cord Injury Using Machine Learning.

PURPOSE: Traumatic cervical spinal cord injury (TCSCI) frequently necessitates mechanical ventilation, and early tracheostomy has been shown to reduce...

Machine Learning-Based Risk Stratification Model to Guide Cardiopulmonary Exercise Training in Cardiovascular Patients.

PURPOSE: In cardiovascular patients, precise risk stratification is crucial for minimizing exercise-related risks and optimizing treatment efficacy du...

Estimation of pulmonary function from time-resolved dynamic chest radiography using machine learning in patients with respiratory disease.

BACKGROUND: Pulmonary function tests (PFTs), particularly spirometry, are the reference standard for assessing airflow limitation in respiratory disea...

Modular RNA-seq Analytics for Exploratory Biomarker Discovery using Public Data.

Publicly available RNA sequencing (RNA-seq) data provide a cost-effective springboard for biomarker discovery. However, heterogeneity across studies o...