Critical Care

Fusing satellite imagery and ground-based observations for PM air pollution modeling in Iran using a deep learning approach.

With the rapid advancement of urbanization and industrialization in cities, air pollution has become one of the significant environmental challenges and issues in many countries. The concentration of particulate matter with an aerodynamic diameter of less than 2.5 µm (PM), recognized as the main air pollutant in Iran, penetrates the respiratory system through inhalation, causing respiratory and ca...

Survival analysis for sepsis patients: A machine learning approach to feature selection and predictive modeling.

Sepsis is a life-threatening condition that presents substantial challenges to healthcare and pharmacological management due to its high mortality rates and complex patient responses. Accurately predicting patient outcomes is essential for optimizing therapeutic interventions and improving clinical decision-making. This study evaluates the predictive performance of the Cox proportional hazards mod...

Automatic melanoma detection using an optimized five-stream convolutional neural network.

Melanoma is among the deadliest forms of malignant skin cancer, with the number of cases increasing dramatically worldwide. Its early and accurate dia...

Hybrid transfer learning and self-attention framework for robust MRI-based brain tumor classification.

Brain tumors are a significant contributor to cancer-related deaths worldwide. Accurate and prompt detection is crucial to reduce mortality rates and ...

An explainable multi-task deep learning framework for crash severity prediction using multi-source data.

Traffic accidents pose significant global challenges, causing substantial injuries, fatalities, and economic losses. Current research predominantly fo...

Profiling short-term longitudinal severity progression and associated genes in COVID-19 patients using EHR and single-cell analysis.

Here we propose CovSF, a deep learning model designed to track and forecast short-term severity progression of COVID-19 patients using longitudinal cl...

Implicit bias in ICU electronic health record data: measurement frequencies and missing data rates of clinical variables.

BACKGROUND: Systematic disparities in data collection within electronic health records (EHRs), defined as non-random patterns in the measurement and r...

Deep learning-based cough classification using application-recorded sounds: a transfer learning approach with VGGish.

BACKGROUND: Coughing sounds contain various bio-metric information with regards to respiratory diseases that can help in the assessment of respiratory...

Machine learning for detection of diffusion abnormalities-related respiratory changes among normal, overweight, and obese individuals based on BMI and pulmonary ventilation parameters: an observational study.

BACKGROUND: The integration of machine learning (ML) algorithms enables the detection of diffusion abnormalities-related respiratory changes in indivi...

A Review of Medical Oxygen Concentrators for Respiratory Applications.

Medical oxygen concentrators are vital apparatuses that deliver supplemental oxygen to persons with hypoxemia. This narrative review provides a review...

A Wearable AI-Driven Mask with Humidity-Sensing Respiratory Microphone for Non-Vocal Communication.

Hoarseness and dysphonia caused by vocal cord conditions or laryngeal surgeries significantly hinder communication and quality of life. This study pre...

[Early warning scores: a rapid umbrella review].

BACKGROUND: Early warning scores (EWS) are used for monitoring and evaluating vital signs in hospitalized patients. With EWS, escalating measures for ...

Leveraging large language models for patient-ventilator asynchrony detection.

OBJECTIVES: The objective of this study is to evaluate whether large language models (LLMs) can achieve performance comparable to expert-developed dee...

Integrating multi-omics and machine learning for disease resistance prediction in legumes.

Multi-omics assisted prediction of disease resistance mechanisms using machine learning has the potential to accelerate the breeding of resistant legu...

European Respiratory Society Clinical Practice Guideline on Telemedicine in Home Mechanical Ventilation.

BACKGROUND: With the increasing prevalence of patients on home mechanical ventilation (HMV), changing indications, shortage of hospital resources, and...

Development and Validation of Machine Learning Models for Predicting 7-Day Mortality in Critically Ill Patients with Traumatic Spinal Cord Injury: A Multicenter Retrospective Study.

BACKGROUND: Traumatic spinal cord injury (TSCI), a severe central nervous system injury, despite treatment advances, critically ill patients with TSCI...

Comprehensive analysis and experimental validation of BST1 as a novel diagnostic biomarker for pediatric sepsis using multiple machine learning algorithms.

Bone marrow stromal cell antigen-1 (BST1) expression is elevated in a variety of human diseases, but its relationship with pediatric sepsis is unclear...

Personalized machine learning models for noninvasive hypoglycemia detection in people with type 1 diabetes using a smartwatch: Insights into feature importance during waking and sleeping times.

Hypoglycemia is a major challenge for people with diabetes. Therefore, glycemic monitoring is an important aspect of diabetes management. However, cur...

A Machine Learning Analysis of Physiological Monitoring Signals to Detect Small Airway Narrowing Due to Cold Air Exposure in Asthma.

Asthma is a chronic inflammatory disease of the small airways, affecting over 200 million people globally. Cold air exposure is a potential risk facto...

A Comparative Assessment of Large Language Models in Pediatric Dialysis: Reliability, Quality and Readability.

INTRODUCTION: This study evaluated the reliability, quality, and readability of ChatGPT (OpenAI, San Francisco, CA), Gemini (Google, Mountain View, CA...