Pulmonology

Predicting lethal courses in critically ill COVID-19 patients using a machine learning model trained on patients with non-COVID-19 viral pneumonia.

In a pandemic with a novel disease, disease-specific prognosis models are available only with a dela...

An Updated Review of Computer-Aided Drug Design and Its Application to COVID-19.

The recent outbreak of the deadly coronavirus disease 19 (COVID-19) pandemic poses serious health co...

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

Semi-Automated Determination of Heavy Metals in Autopsy Tissue Using Robot-Assisted Sample Preparation and ICP-MS.

The endoprosthetic care of hip and knee joints introduces multiple materials into the human body. Me...

Deep learning for semi-automated unidirectional measurement of lung tumor size in CT.

BACKGROUND: Performing Response Evaluation Criteria in Solid Tumor (RECISTS) measurement is a non-tr...

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 bene...

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 respirato...

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...

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-connect...

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 ...

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 ...

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-...

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 indepe...

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 mortali...

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...

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 signific...

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 a...

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 ...

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

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

Human Breast Milk (HBM) is a storehouse of micronutrients, macronutrients, immune factors, microbiot...

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 inconsis...