Critical Care

3D CT-Inclusive Deep-Learning Model to Predict Mortality, ICU Admittance, and Intubation in COVID-19 Patients.

Chest CT is a useful initial exam in patients with coronavirus disease 2019 (COVID-19) for assessing...

Mortality prediction in ICU Using a Stacked Ensemble Model.

Artificial intelligence (AI) technology has huge scope in developing models to predict the survival ...

A Proactive Attack Detection for Heating, Ventilation, and Air Conditioning (HVAC) System Using Explainable Extreme Gradient Boosting Model (XGBoost).

The advent of Industry 4.0 has revolutionized the life enormously. There is a growing trend towards ...

Deep MCANC: A deep learning approach to multi-channel active noise control.

Traditional multi-channel active noise control (MCANC) is based on adaptive filtering and usually us...

Development and validation of a mathematical model to simulate human cardiovascular and respiratory responses to battlefield trauma.

Mathematical models of human cardiovascular and respiratory systems provide a viable alternative to ...

Identification of two robust subclasses of sepsis with both prognostic and therapeutic values based on machine learning analysis.

BACKGROUND: Sepsis is a heterogeneous syndrome with high morbidity and mortality. Optimal and effect...

A systematic review: Chest radiography images (X-ray images) analysis and COVID-19 categorization diagnosis using artificial intelligence techniques.

COVID-19 pandemic created a turmoil across nations due to Severe Acute Respiratory Syndrome Corona v...

Machine learning-enabled nanosafety assessment of multi-metallic alloy nanoparticles modified TiO system.

Establishing toxicological predictive modeling frameworks for heterogeneous nanomaterials is crucial...

Style-transfer counterfactual explanations: An application to mortality prevention of ICU patients.

In recent years, machine learning methods have been rapidly adopted in the medical domain. However, ...

Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.

Coronary artery disease (CAD) is a cardiovascular condition with high morbidity and mortality. Intra...

Deep Learning Anomaly Classification Using Multi-Attention Residual Blocks for Industrial Control Systems.

This paper proposes a novel method monitoring network packets to classify anomalies in industrial co...

A Fuzzy Neural Network-Based Evaluation Method for Physical Education Teaching Management in Colleges.

A novel Fuzzy Neural Network (FNN) teaching quality assessment model of physical education (PE) is p...

Multi-modal wound classification using wound image and location by deep neural network.

Wound classification is an essential step of wound diagnosis. An efficient classifier can assist wou...

Multi-center, multi-vendor validation of deep learning-based attenuation correction in SPECT MPI: data from the international flurpiridaz-301 trial.

PURPOSE: Although SPECT myocardial perfusion imaging (MPI) is susceptible to artifacts from soft tis...

Multi-Perspective Hierarchical Deep-Fusion Learning Framework for Lung Nodule Classification.

Lung cancer is the leading cancer type that causes mortality in both men and women. Computer-aided d...

Graph based multi-scale neighboring topology deep learning for kidney and tumor segmentation.

Effective learning and modelling of spatial and semantic relations between image regions in various ...

Invited Commentary: Postoperative Artificial Intelligence Model for ICU Triage.

GLSNN Network: A Multi-Scale Spatiotemporal Prediction Model for Urban Traffic Flow.

Traffic flow prediction is a key issue in intelligent transportation systems. The growing trend in d...

A Dual-Channel Deep Learning Approach for Lung Cavity Estimation From Hyperpolarized Gas and Proton MRI.

BACKGROUND: Hyperpolarized gas MRI can quantify regional lung ventilation via biomarkers, including ...

Real-time monitoring of air pathogens in the ICU with biosensors and robots.

An integrated ELECTRE method for selection of rehabilitation center with m-polar fuzzy N-soft information.

The primary goal of this research article is to apply ELECTRE I, a fundamental multi-criteria group ...