Pulmonology

Utility of convolutional neural network-based algorithm in medical images for liver fibrosis assessment.

Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.

Identification of those at greatest risk of death due to the substantial threat of COVID-19 can benefit from novel approaches to epidemiology that leverage large datasets and complex machine-learning models, provide data-driven intelligence, and guide decisions such as intensive-care unit admission (ICUA). The objective of this study is two-fold, one substantive and one methodological: substantive...

Adaptive Fuzzy Sliding Mode Control of a Pressure-Controlled Artificial Ventilator.

This paper presents the application of adaptive fuzzy sliding mode control (AFSMC) for the respiratory system to assist the patients facing difficulty...

COVID-19 deep classification network based on convolution and deconvolution local enhancement.

Computer Tomography (CT) detection can effectively overcome the problems of traditional detection of Corona Virus Disease 2019 (COVID-19), such as lag...

Choquet fuzzy integral-based classifier ensemble technique for COVID-19 detection.

The COVID-19 outbreak has resulted in a global pandemic and led to more than a million deaths to date. COVID-19 early detection is essential for its m...

Detection of the location of pneumothorax in chest X-rays using small artificial neural networks and a simple training process.

The purpose of this study was to evaluate the diagnostic performance achieved by using fully-connected small artificial neural networks (ANNs) and a s...

Deep learning for classification of pediatric chest radiographs by WHO's standardized methodology.

BACKGROUND: The World Health Organization (WHO)-defined radiological pneumonia is a preferred endpoint in pneumococcal vaccine efficacy and effectiven...

Machine learning-based CT radiomics features for the prediction of pulmonary metastasis in osteosarcoma.

OBJECTIVE: This study aims to build machine learning-based CT radiomic features to predict patients developing metastasis after osteosarcoma diagnosis...

Prediction of venous thromboembolism with machine learning techniques in young-middle-aged inpatients.

Accumulating studies appear to suggest that the risk factors for venous thromboembolism (VTE) among young-middle-aged inpatients are different from th...

Detecting COVID-19 in Chest X-Ray Images via MCFF-Net.

COVID-19 is a respiratory disease caused by severe acute respiratory syndrome coronavirus (SARS-CoV-2). Due to the rapid spread of COVID-19 around the...

Multivariable mortality risk prediction using machine learning for COVID-19 patients at admission (AICOVID).

In Coronavirus disease 2019 (COVID-19), early identification of patients with a high risk of mortality can significantly improve triage, bed allocatio...

Identifying Patient-Ventilator Asynchrony on a Small Dataset Using Image-Based Transfer Learning.

Mechanical ventilation is an essential life-support treatment for patients who cannot breathe independently. Patient-ventilator asynchrony (PVA) occur...

Distinguishing nontuberculous mycobacteria from Mycobacterium tuberculosis lung disease from CT images using a deep learning framework.

PURPOSE: To develop and evaluate the effectiveness of a deep learning framework (3D-ResNet) based on CT images to distinguish nontuberculous mycobacte...

Deep learning for noninvasive liver fibrosis classification: A systematic review.

BACKGROUND AND AIMS: While biopsy is the gold standard for liver fibrosis staging, it poses significant risks. Noninvasive assessment of liver fibrosi...

Application of machine learning to large in-vitro databases to identify cancer cell characteristics: telomerase reverse transcriptase (TERT) expression.

Advances in biotechnology and machine learning have created an enhanced environment for unearthing and exploiting previously unrecognized relationship...

Artificial intelligence-powered remote monitoring of patients with chronic obstructive pulmonary disease.

Radiomics side experiments and DAFIT approach in identifying pulmonary hypertension using Cardiac MRI derived radiomics based machine learning models.

Side experiments are performed on radiomics models to improve their reproducibility. We measure the impact of myocardial masks, radiomic side experime...

Human breast milk-based nutritherapy: A blueprint for pediatric healthcare.

Human Breast Milk (HBM) is a storehouse of micronutrients, macronutrients, immune factors, microbiota and numerous other bioactive macromolecules. Ful...

Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index.

Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood...

Transfer learning-based approach for detecting COVID-19 ailment in lung CT scan.

This research work aims to identify COVID-19 through deep learning models using lung CT-SCAN images. In order to enhance lung CT scan efficiency, a su...