Pulmonology

Automatic opportunistic osteoporosis screening using low-dose chest computed tomography scans obtained for lung cancer screening.

OBJECTIVE: Osteoporosis is a prevalent and treatable condition, but it remains underdiagnosed. In th...

Artificial Intelligence in Respiratory Diseases.

Radiogenomic Models Using Machine Learning Techniques to Predict EGFR Mutations in Non-Small Cell Lung Cancer.

BACKGROUND: The purpose of this study was to build radiogenomics models from texture signatures deri...

Deep learning for screening of interstitial lung disease patterns in high-resolution CT images.

AIM: To develop a screening tool for the detection of interstitial lung disease (ILD) patterns using...

Evaluation of acute pulmonary embolism and clot burden on CTPA with deep learning.

OBJECTIVES: To take advantage of the deep learning algorithms to detect and calculate clot burden of...

Essential oils against bacterial isolates from cystic fibrosis patients by means of antimicrobial and unsupervised machine learning approaches.

Recurrent and chronic respiratory tract infections in cystic fibrosis (CF) patients result in progre...

Comparison of medium-term survival outcomes between robot-assisted thoracoscopic surgery and video-assisted thoracoscopic surgery in treating primary lung cancer.

OBJECTIVES: Robot-assisted thoracoscopic surgery (RATS) for primary lung cancer has been spreading r...

Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer.

INTRODUCTION: The aim of the study was to extract anthropometric measures from CT by deep learning a...

CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.

OBJECTIVES: To evaluate the deep learning models for differentiating invasive pulmonary adenocarcino...

Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.

OBJECTIVES: To evaluate whether the liver and spleen volumetric indices, measured on portal venous p...

Hybrid decision tree-based machine learning models for short-term water quality prediction.

Water resources are the foundation of people's life and economic development, and are closely relate...

Robotic assisted transaxillary thymectomy: Novel approach to thymic surgery.

BACKGROUND: We present a video case with a novel, minimally invasive approach to the thymus, which d...

Diagnosis of ventilator-associated pneumonia using electronic nose sensor array signals: solutions to improve the application of machine learning in respiratory research.

BACKGROUND: Ventilator-associated pneumonia (VAP) is a significant cause of mortality in the intensi...

Combined Use of Three Machine Learning Modeling Methods to Develop a Ten-Gene Signature for the Diagnosis of Ventilator-Associated Pneumonia.

BACKGROUND This study aimed to use three modeling methods, logistic regression analysis, random fore...

Towards automated generation of curated datasets in radiology: Application of natural language processing to unstructured reports exemplified on CT for pulmonary embolism.

PURPOSE: To design and evaluate a self-trainable natural language processing (NLP)-based procedure t...

Machine learning for syndromic surveillance using veterinary necropsy reports.

The use of natural language data for animal population surveillance represents a valuable opportunit...

Cenicriviroc, a dual CCR2 and CCR5 antagonist leads to a reduction in plasma fibrotic biomarkers in persons living with HIV on antiretroviral therapy.

Chronic HIV is associated with increased inflammation and tissue fibrosis despite suppressive antir...

Novel biomarker genes which distinguish between smokers and chronic obstructive pulmonary disease patients with machine learning approach.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is combination of progressive lung diseases...

Mixed-integer optimization approach to learning association rules for unplanned ICU transfer.

After admission to emergency department (ED), patients with critical illnesses are transferred to in...

Technical Note: 3D localization of lung tumors on cone beam CT projections via a convolutional recurrent neural network.

PURPOSE: To design a convolutional recurrent neural network (CRNN) that calculates three-dimensional...

A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation.

PURPOSE: The purpose of this study is to develop a deep learning (DL) method for producing four-dime...