Pulmonology

Latest AI and machine learning research in pulmonology for healthcare professionals.

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A New Optimal Diagnosis System for Coronavirus (COVID-19) Diagnosis Based on Archimedes Optimization Algorithm on Chest X-Ray Images.

The new coronavirus, COVID-19, has affected people all over the world. Coronaviruses are a large gro...

Nasopharyngeal metabolomics and machine learning approach for the diagnosis of influenza.

BACKGROUND: Respiratory virus infections are significant causes of morbidity and mortality, and may ...

A machine learning approach to predict extreme inactivity in COPD patients using non-activity-related clinical data.

Facilitating the identification of extreme inactivity (EI) has the potential to improve morbidity an...

Piezoelectric Smart Patch Operated with Machine-Learning Algorithms for Effective Detection and Elimination of Condensation.

Timely detection and elimination of surface condensation is crucial for diverse applications in agri...

Cancer-associated fibroblasts are associated with poor prognosis in solid type of lung adenocarcinoma in a machine learning analysis.

Cancer-associated fibroblasts (CAFs) participate in critical processes in the tumor microenvironment...

Machine learning for manually-measured water quality prediction in fish farming.

Monitoring variables such as dissolved oxygen, pH, and pond temperature is a key aspect of high-qual...

CXCL1: A new diagnostic biomarker for human tuberculosis discovered using Diversity Outbred mice.

More humans have died of tuberculosis (TB) than any other infectious disease and millions still die ...

Evaluation of the Effectiveness of Artificial Intelligence Chest CT Lung Nodule Detection Based on Deep Learning.

Lung cancer is one of the most malignant tumors. If it can be detected early and treated actively, i...

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung canc...

Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital.

AIM: To evaluate a deep-learning-based computer-aided detection (DL-CAD) software system for pulmona...

Deep-learning based detection of COVID-19 using lung ultrasound imagery.

BACKGROUND: The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, es...

Interleukin-37 gene polymorphism and susceptibility to pulmonary tuberculosis among Iraqi patients.

BACKGROUND: Control of tuberculosis (TB) depends on a balance between host's immune factors and bact...

Estimated Artificial Neural Network Modeling of Maximal Oxygen Uptake Based on Multistage 10-m Shuttle Run Test in Healthy Adults.

We aimed to develop an artificial neural network (ANN) model to estimate the maximal oxygen uptake (...

A case of fatal multidrug intoxication involving flualprazolam: distribution in body fluids and solid tissues.

PURPOSE: Designer benzodiazepines (DBZDs) increasingly emerged on the novel psychoactive substance (...

A Method for Optimal Detection of Lung Cancer Based on Deep Learning Optimized by Marine Predators Algorithm.

Lung cancer is the uncontrolled growth of cells in the lung that are made up of two spongy organs lo...

Scalable quorum-based deep neural networks with adversarial learning for automated lung lobe segmentation in fast helical free-breathing CTs.

PURPOSE: Fast helical free-breathing CT (FHFBCT) scans are widely used for 5DCT and 5D Cone Beam ima...

Application of Artificial Intelligence for Diagnosis and Risk Stratification in NAFLD and NASH: The State of the Art.

The diagnosis of nonalcoholic fatty liver disease and associated fibrosis is challenging given the l...

Shape-Sensing Robotic-Assisted Bronchoscopy in the Diagnosis of Pulmonary Parenchymal Lesions.

BACKGROUND: The landscape of guided bronchoscopy for the sampling of pulmonary parenchymal lesions i...

Optimal number of strong labels for curriculum learning with convolutional neural network to classify pulmonary abnormalities in chest radiographs.

BACKGROUND AND OBJECTIVE: It is important to alleviate annotation efforts and costs by efficiently t...

Explainable DCNN based chest X-ray image analysis and classification for COVID-19 pneumonia detection.

To speed up the discovery of COVID-19 disease mechanisms by X-ray images, this research developed a ...

Deep learning and lung ultrasound for Covid-19 pneumonia detection and severity classification.

The Covid-19 European outbreak in February 2020 has challenged the world's health systems, eliciting...

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