Pulmonology

Deep-learning algorithm helps to standardise ATS/ERS spirometric acceptability and usability criteria.

RATIONALE: While American Thoracic Society (ATS)/European Respiratory Society (ERS) quality control criteria for spirometry include several quantitative limits, it also requires manual visual inspection. The current approach is time consuming and leads to high intertechnician variability. We propose a deep-learning approach called convolutional neural network (CNN), to standardise spirometric mano...

Quantification of Cystic Fibrosis Lung Disease with Radiomics-based CT Scores.

PURPOSE: To develop radiomics-based CT scores for assessing lung disease severity and exacerbation risk in adult patients with cystic fibrosis (CF).

Hemodynamic Characteristics and Outcomes of Pulmonary Hypertension in Patients Undergoing Tricuspid Valve Repair or Replacement.

BACKGROUND: The impact of pulmonary hypertension (PH) on outcomes after surgical tricuspid valve replacement (TVR) and repair (TVr) is unclear. We sou...

Next-Generation Bioelectric Medicine: Harnessing the Therapeutic Potential of Neural Implants.

Bioelectric medicine leverages natural signaling pathways in the nervous system to counteract organ dysfunction. This novel approach has potential to ...

Fusion Learning on Multiple-Tag RFID Measurements for Respiratory Rate Monitoring.

Future advances in the medical Internet of Things (IoT) will require sensors that are unobtrusive and passively powered. With the use of wireless, wea...

NSCR-Based DenseNet for Lung Tumor Recognition Using Chest CT Image.

Nonnegative sparse representation has become a popular methodology in medical analysis and diagnosis in recent years. In order to resolve network degr...

Fully Automatic Atrial Fibrosis Assessment Using a Multilabel Convolutional Neural Network.

BACKGROUND: Pathological atrial fibrosis is a major contributor to sustained atrial fibrillation. Currently, late gadolinium enhancement (LGE) scans p...

Optimised genetic algorithm-extreme learning machine approach for automatic COVID-19 detection.

The coronavirus disease (COVID-19), is an ongoing global pandemic caused by severe acute respiratory syndrome. Chest Computed Tomography (CT) is an ef...

Prediction of in-hospital mortality in patients on mechanical ventilation post traumatic brain injury: machine learning approach.

BACKGROUND: The study aimed to introduce a machine learning model that predicts in-hospital mortality in patients on mechanical ventilation (MV) follo...

Artificial Intelligence Applied to Chest X-Ray Images for the Automatic Detection of COVID-19. A Thoughtful Evaluation Approach.

Current standard protocols used in the clinic for diagnosing COVID-19 include molecular or antigen tests, generally complemented by a plain chest X-Ra...

Artificial intelligence in the diagnosis of pediatric allergic diseases.

Artificial intelligence (AI) is a field of data science pertaining to advanced computing machines capable of learning from data and interacting with t...

3D deep learning based classification of pulmonary ground glass opacity nodules with automatic segmentation.

Classifying ground-glass lung nodules (GGNs) into atypical adenomatous hyperplasia (AAH), adenocarcinoma in situ (AIS), minimally invasive adenocarcin...

Predicting potential residues associated with lung cancer using deep neural network.

Lung cancer is a prominent type of cancer, which leads to high mortality rate worldwide. The major lung cancers lung adenocarcinoma (LUAD) and lung sq...

Motion-flow-guided recurrent network for respiratory signal estimation of x-ray angiographic image sequences.

Motion compensation can eliminate inconsistencies of respiratory movement during image acquisitions for precise vascular reconstruction in the clinica...

Identification of biological correlates associated with respiratory failure in COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a global public health concern. Recently, a genome-wide association study (GWAS) was performed with...

Quality control, HPTLC analysis, antioxidant and antimicrobial activity of hydroalcoholic extract of roots of ( C.B Clarke).

OBJECTIVES: , CB Clarke () is a perennial herb of the Compositae family. The root of has been used for the treatment of various diseases such as hepa...

Artificial intelligence-based imaging analytics and lung cancer diagnostics: Considerations for health system leaders.

Lung cancer is a leading cause of cancer death in Canada, and accurate, early diagnosis are critical to improving clinical outcomes. Artificial Intell...

Five novel clinical phenotypes for critically ill patients with mechanical ventilation in intensive care units: a retrospective and multi database study.

BACKGROUND: Although protective mechanical ventilation (MV) has been used in a variety of applications, lung injury may occur in both patients with an...

Hybrid-COVID: a novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray images.

The novel Coronavirus disease (COVID-19), which first appeared at the end of December 2019, continues to spread rapidly in most countries of the world...

A large-scale internal validation study of unsupervised virtual trichrome staining technologies on nonalcoholic steatohepatitis liver biopsies.

Non-alcoholic steatohepatitis (NASH) is a fatty liver disease characterized by accumulation of fat in hepatocytes with concurrent inflammation and is ...