Pulmonology

Detection of COVID-19 from Chest X-ray Images Using Deep Convolutional Neural Networks.

The COVID-19 global pandemic has wreaked havoc on every aspect of our lives. More specifically, healthcare systems were greatly stretched to their limits and beyond. Advances in artificial intelligence have enabled the implementation of sophisticated applications that can meet clinical accuracy requirements. In this study, customized and pre-trained deep learning models based on convolutional neur...

Research on Key Algorithms of the Lung CAD System Based on Cascade Feature and Hybrid Swarm Intelligence Optimization for MKL-SVM.

Feature selection and lung nodule recognition are the core modules of the lung computer-aided detection (Lung CAD) system. To improve the performance of the Lung CAD system, algorithmic research is carried out for the above two parts, respectively. First, in view of the poor interpretability of deep features and the incomplete expression of clinically defined handcrafted features, a feature cascad...

Identifying Outstanding Transition-Metal-Alloy Heterogeneous Catalysts for the Oxygen Reduction and Evolution Reactions via Subgroup Discovery.

UNLABELLED: In order to estimate the reactivity of a large number of potentially complex heterogeneous catalysts while searching for novel and more ef...

Combining computed tomography and biologically effective dose in radiomics and deep learning improves prediction of tumor response to robotic lung stereotactic body radiation therapy.

PURPOSE: The aim of this study is to improve the performance of machine learning (ML) models in predicting response of non-small cell lung cancer (NSC...

Disease type detection in lung and colon cancer images using the complement approach of inefficient sets.

Lung and colon cancers are deadly diseases that can develop simultaneously in organs and adversely affect human life in some special cases. Although t...

Current and emerging artificial intelligence applications in chest imaging: a pediatric perspective.

Artificial intelligence (AI) applications for chest radiography and chest CT are among the most developed applications in radiology. More than 40 cert...

Vaso reactivity test using inhaled nitric oxide for pulmonary arterial hypertension accompanied by severe interstitial lung disease attributed to systemic sclerosis: A case report.

A 70-year-old man with severe interstitial pneumonia attributed to limited cutaneous systemic sclerosis was referred to our institution because of wor...

Use of a Digital Chronic Obstructive Pulmonary Disease Respiratory Tracker in a Primary Care Setting: A Feasibility Study.

INTRODUCTION: Telemonitoring is a promising self-management strategy to improve health care outcomes. This study evaluated real-world adoption of the ...

Deep Learning for Detection of Pulmonary Metastasis on Chest Radiographs.

Background A computer-aided detection (CAD) system may help surveillance for pulmonary metastasis at chest radiography in situations where there is li...

GraphRegNet: Deep Graph Regularisation Networks on Sparse Keypoints for Dense Registration of 3D Lung CTs.

In the last two years learning-based methods have started to show encouraging results in different supervised and unsupervised medical image registrat...

Contralaterally Enhanced Networks for Thoracic Disease Detection.

Identifying and locating diseases in chest X-rays are very challenging, due to the low visual contrast between normal and abnormal regions, and distor...

Recognition of COVID-19 from CT Scans Using Two-Stage Deep-Learning-Based Approach: CNR-IEMN.

Since the appearance of the COVID-19 pandemic (at the end of 2019, Wuhan, China), the recognition of COVID-19 with medical imaging has become an activ...

GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mt...

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset.

The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by thi...

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecti...

A survey of computer-aided diagnosis of lung nodules from CT scans using deep learning.

Lung cancer has one of the highest mortalities of all cancers. According to the National Lung Screening Trial, patients who underwent low-dose compute...

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.

antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between...

Respiratory sound classification for crackles, wheezes, and rhonchi in the clinical field using deep learning.

Auscultation has been essential part of the physical examination; this is non-invasive, real-time, and very informative. Detection of abnormal respira...

On the Use of Deep Learning for Imaging-Based COVID-19 Detection Using Chest X-rays.

The global COVID-19 pandemic that started in 2019 and created major disruptions around the world demonstrated the imperative need for quick, inexpensi...

3D-PulCNN: Pulmonary cancer classification from hyperspectral images using convolution combination unit based CNN.

Pulmonary cancer is one of the most common malignancies worldwide. Accurate classification of its subtypes is required in differential diagnosis. Howe...