Pulmonology

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

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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....

A comparison of the fusion model of deep learning neural networks with human observation for lung nodule detection and classification.

OBJECTIVES: To compare the diagnostic performance of a newly developed artificial intelligence (AI) ...

Development and validation of consensus machine learning-based models for the prediction of novel small molecules as potential anti-tubercular agents.

Tuberculosis (TB) is an infectious disease and the leading cause of death globally. The rapidly emer...

Machine learning models for classification tasks related to drug safety.

In this review, we outline the current trends in the field of machine learning-driven classification...

Predictive online 3D target tracking with population-based generative networks for image-guided radiotherapy.

PURPOSE: Respiratory motion of thoracic organs poses a severe challenge for the administration of im...

Weighing features of lung and heart regions for thoracic disease classification.

BACKGROUND: Chest X-rays are the most commonly available and affordable radiological examination for...

Does machine learning have a role in the prediction of asthma in children?

Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide ...

Deep Learning on Chest X-ray Images to Detect and Evaluate Pneumonia Cases at the Era of COVID-19.

Coronavirus disease 2019 (COVID-19) is an infectious disease with first symptoms similar to the flu....

COVID-19 pneumonia on chest X-rays: Performance of a deep learning-based computer-aided detection system.

Chest X-rays (CXRs) can help triage for Coronavirus disease (COVID-19) patients in resource-constrai...

Subcarinal Lymph Node Dissection in Solo Robot-assisted Thoracic Surgery.

The surgical instruments used in robot-assisted thoracic surgery are flexible to enable the surgeon ...

AI-based improvement in lung cancer detection on chest radiographs: results of a multi-reader study in NLST dataset.

OBJECTIVE: Assess if deep learning-based artificial intelligence (AI) algorithm improves reader perf...

Natural Language Processing to Identify Pulmonary Nodules and Extract Nodule Characteristics From Radiology Reports.

BACKGROUND: There is an urgent need for population-based studies on managing patients with pulmonary...

An Overview of Deep Learning Techniques on Chest X-Ray and CT Scan Identification of COVID-19.

Pneumonia is an infamous life-threatening lung bacterial or viral infection. The latest viral infect...

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premat...

Ensemble machine learning of factors influencing COVID-19 across US counties.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) the causal agent for COVID-19, is a com...

Lung Lesion Localization of COVID-19 From Chest CT Image: A Novel Weakly Supervised Learning Method.

Chest computed tomography (CT) image data is necessary for early diagnosis, treatment, and prognosis...

Integration of CNN, CBMIR, and Visualization Techniques for Diagnosis and Quantification of Covid-19 Disease.

Diagnosis techniques based on medical image modalities have higher sensitivities compared to convent...

Design Comorbidity Portfolios to Improve Treatment Cost Prediction of Asthma Using Machine Learning.

Comorbidity is an important factor to consider when trying to predict the cost of treating asthma pa...

Enhanced Diagnosis of Pneumothorax with an Improved Real-Time Augmentation for Imbalanced Chest X-rays Data Based on DCNN.

Pneumothorax is a common pulmonary disease that can lead to dyspnea and can be life-threatening. X-r...

A long short-term memory-fully connected (LSTM-FC) neural network for predicting the incidence of bronchopneumonia in children.

Bronchopneumonia is the most common infectious disease in children, and it seriously endangers child...

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