Pulmonology

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

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The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting r...

Using trauma registry data to predict prolonged mechanical ventilation in patients with traumatic brain injury: Machine learning approach.

OBJECTIVES: We aimed to build a machine learning predictive model to predict the risk of prolonged m...

Predicting the chemical reactivity of organic materials using a machine-learning approach.

Stability and compatibility between chemical components are essential parameters that need to be con...

Machine learning-based prediction of acute severity in infants hospitalized for bronchiolitis: a multicenter prospective study.

We aimed to develop machine learning models to accurately predict bronchiolitis severity, and to com...

A deep learning approach to characterize 2019 coronavirus disease (COVID-19) pneumonia in chest CT images.

OBJECTIVES: To utilize a deep learning model for automatic detection of abnormalities in chest CT im...

Automated labeling of the airway tree in terms of lobes based on deep learning of bifurcation point detection.

This paper presents an automatic lobe-based labeling of airway tree method, which can detect the bif...

Pulmonary Embolism at CT Pulmonary Angiography in Patients with COVID-19.

PURPOSE: To evaluate pulmonary embolism (PE) prevalence at CT pulmonary angiography in patients test...

Histological Subtypes Classification of Lung Cancers on CT Images Using 3D Deep Learning and Radiomics.

RATIONALE AND OBJECTIVES: Histological subtypes of lung cancers are critical for clinical treatment ...

Pneumonia Detection in Chest X-Ray Dose-Equivalent CT: Impact of Dose Reduction on Detectability by Artificial Intelligence.

RATIONALE AND OBJECTIVES: There has been a significant increase of immunocompromised patients in rec...

Intraoperative complications and troubles in robot-assisted anatomical pulmonary resection.

OBJECTIVE: Regarding intraoperative complications and troubles during robot-assisted thoracic surger...

The major effects of health-related quality of life on 5-year survival prediction among lung cancer survivors: applications of machine learning.

The primary goal of this study was to evaluate the major roles of health-related quality of life (HR...

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study.

The COVID-19 pandemia due to the SARS-CoV-2 coronavirus, in its first 4 months since its outbreak, h...

Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison.

OBJECTIVE: This study determined the effect of dose reduction and kernel selection on quantifying em...

COVID-19 Pneumonia Diagnosis Using a Simple 2D Deep Learning Framework With a Single Chest CT Image: Model Development and Validation.

BACKGROUND: Coronavirus disease (COVID-19) has spread explosively worldwide since the beginning of 2...

Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based ...

An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall surv...

Truncated inception net: COVID-19 outbreak screening using chest X-rays.

Since December 2019, the Coronavirus Disease (COVID-19) pandemic has caused world-wide turmoil in a ...

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

In personalized medicine, many factors influence the choice of compounds. Hence, the selection of su...

A machine learning-based framework for Predicting Treatment Failure in tuberculosis: A case study of six countries.

Tuberculosis is ranked as the 2nd deadliest disease in the world and is responsible for ten million ...

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