Pulmonology

Comparison of serum biochemical markers in patients with mesothelioma and pleural plaques versus healthy individuals exposed to environmental asbestos.

BACKGROUND: In this study, we aimed to compare serum biochemical markers in patients with malignant pleural mesothelioma and pleural plaques versus healthy individuals exposed to environmental asbestos.

Using machine learning to examine the relationship between asthma and absenteeism.

In this study, we found that machine learning was able to effectively estimate student learning outcomes geo-spatially across all the campuses in a large, urban, independent school district. The machine learning showed that key factors in estimating the student learning outcomes included the number of days students were absent from school. In turn, one of the most important factors in estimating t...

Respiratory Sound Based Classification of Chronic Obstructive Pulmonary Disease: a Risk Stratification Approach in Machine Learning Paradigm.

This article investigates the classification of normal and COPD subjects on the basis of respiratory sound analysis using machine learning techniques....

A case of robotic assisted percutaneous coronary intervention of the left main coronary artery in a patient with very late baffle stenosis after surgical correction of anomalous left coronary artery from the pulmonary artery.

A 34-year-old woman with history of surgical correction (Takeuchi procedure) of anomalous left coronary artery from the pulmonary artery (ALCAPA) pres...

An image-based deep learning framework for individualizing radiotherapy dose.

BACKGROUND: Radiotherapy continues to be delivered uniformly without consideration of individual tumor characteristics. To advance toward more precise...

Automatic Multi-Level In-Exhale Segmentation and Enhanced Generalized S-Transform for wheezing detection.

BACKGROUND AND OBJECTIVE: Wheezing is a common symptom of patients caused by asthma and chronic obstructive pulmonary diseases. Wheezing detection ide...

Object Detection During Newborn Resuscitation Activities.

OBJECTIVE: Birth asphyxia is a major newborn mortality problem in low-resource countries. International guideline provides treatment recommendations; ...

Feasibility of Natural Language Processing-Assisted Auditing of Critical Findings in Chest Radiology.

OBJECTIVE: Time-sensitive communication of critical imaging findings like pneumothorax or pulmonary embolism to referring physicians is essential for ...

Automated detection of third molars and mandibular nerve by deep learning.

The approximity of the inferior alveolar nerve (IAN) to the roots of lower third molars (M3) is a risk factor for the occurrence of nerve damage and s...

Classification of benign and malignant lung nodules from CT images based on hybrid features.

The classification of benign and malignant lung nodules has great significance for the early detection of lung cancer, since early diagnosis of nodule...

Diagnostic value of spirometry vs impulse oscillometry: A comparative study in children with sickle cell disease.

BACKGROUND: Spirometry is conventionally used to diagnose airway diseases in children with sickle cell disease (C-SCD). However, spirometry is difficu...

Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses.

Background Intratumor heterogeneity in lung cancer may influence outcomes. CT radiomics seeks to assess tumor features to provide detailed imaging fea...

Conservation region finding for influenza A viruses by machine learning methods of N-linked glycosylation sites and B-cell epitopes.

Influenza type A, a serious infectious disease of the human respiratory tract, poses an enormous threat to human health worldwide. It leads to high mo...

One-lung ventilation duration-dependent stress response in thoracotomies and the effect of a low-volume, high-frequency differentiated ventilation strategy on this response.

BACKGROUND: This study aims to investigate the effect of ventilation of the non-ventilated lung in patients undergoing one-lung ventilation by a separ...

Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications.

Artificial intelligence (AI) has been present in some guise within the field of radiology for over 50 years. The first studies investigating computer-...

Fusing learned representations from Riesz Filters and Deep CNN for lung tissue classification.

A novel method to detect and classify several classes of diseased and healthy lung tissue in CT (Computed Tomography), based on the fusion of Riesz an...

A cascaded dual-pathway residual network for lung nodule segmentation in CT images.

It is difficult to obtain an accurate segmentation due to the variety of lung nodules in computed tomography (CT) images. In this study, we propose a ...

Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT.

PURPOSE: Computed tomography (CT) is an effective method for detecting and characterizing lung nodules in vivo. With the growing use of chest CT, the ...

Development of Adverse Outcome Pathway for PPARγ Antagonism Leading to Pulmonary Fibrosis and Chemical Selection for Its Validation: ToxCast Database and a Deep Learning Artificial Neural Network Model-Based Approach.

Exposure to certain chemicals such as disinfectants through inhalation is suspected to be involved in the development of pulmonary fibrosis, a lung di...

An automatic method for lung segmentation and reconstruction in chest X-ray using deep neural networks.

BACKGROUND AND OBJECTIVE: Chest X-ray (CXR) is one of the most used imaging techniques for detection and diagnosis of pulmonary diseases. A critical c...