Pulmonology

Comparison of the Abbott Architect BRAHMS and the Biomérieux Vidas BRAHMS Procalcitonin Assays.

BACKGROUND: Procalcitonin (PCT) is a well-established marker for bacterial infection. Recently the US Food and Drug Administration approved the expanded use of this biomarker to guide clinical decisions for antibiotic treatment in patients with lower respiratory tract infections. Both the Architect BRAHMS PCT (PCT-A) and Vidas BRAHMS PCT (PCT-V) are approved for this indication. The aim of this st...

Deep learning and the evaluation of pulmonary fibrosis.

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.

BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the co...

Bounded Fuzzy Possibilistic Method Reveals Information about Lung Cancer through Analysis of Metabolomics.

Learning methods, such as conventional clustering and classification, have been applied in diagnosing diseases to categorize samples based on their fe...

HLBS-PopOmics: an online knowledge base to accelerate dissemination and implementation of research advances in population genomics to reduce the burden of heart, lung, blood, and sleep disorders.

Recent dramatic advances in multiomics research coupled with exponentially increasing volume, complexity, and interdisciplinary nature of publications...

Convolutional Neural Networks with Template-Based Data Augmentation for Functional Lung Image Quantification.

RATIONALE AND OBJECTIVES: We propose an automated segmentation pipeline based on deep learning for proton lung MRI segmentation and ventilation-based ...

Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver.

Purpose To develop and validate a deep learning system (DLS) for staging liver fibrosis by using CT images in the liver. Materials and Methods DLS for...

Multiparametric ultrasomics of significant liver fibrosis: A machine learning-based analysis.

OBJECTIVE: To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning.

Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.

BACKGROUND AND OBJECTIVE: In pulmonary nodule detection, the first stage, candidate detection, aims to detect suspicious pulmonary nodules. However, d...

Classification of lung adenocarcinoma transcriptome subtypes from pathological images using deep convolutional networks.

PURPOSE: Convolutional neural networks have become rapidly popular for image recognition and image analysis because of its powerful potential. In this...

A Study of Diagnostic Accuracy Using a Chemical Sensor Array and a Machine Learning Technique to Detect Lung Cancer.

Lung cancer is the leading cause of cancer death around the world, and lung cancer screening remains challenging. This study aimed to develop a breath...

Identification of a Novel Clinical Phenotype of Severe Malaria using a Network-Based Clustering Approach.

The parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with antimalarial drugs, more than 400,000 deaths are r...

Ethambutol-induced optic neuropathy in renal disorder: a clinico-electrophysiological study.

OBJECTIVE: To report the spectrum of ethambutol induced optic neuropathy in a group of renal patients with tuberculosis and the role of visual evoked ...

Study on screening potential allergenic proteins from infant milk powders based on human mast cell membrane chromatography and histamine release assays.

Cow's milk allergy is mainly observed in infants and young children. Most allergic reactions affect the skin, followed by the gastrointestinal and res...

Predictors of atrial fibrillation early recurrence following cryoballoon ablation of pulmonary veins using statistical assessment and machine learning algorithms.

Inflammation, oxidative stress, myocardial injury biomarkers and clinical parameters (longer AF duration, left atrial enlargement, the metabolic syndr...

Computer-aided detection in chest radiography based on artificial intelligence: a survey.

As the most common examination tool in medical practice, chest radiography has important clinical value in the diagnosis of disease. Thus, the automat...

Prototype-Based Compound Discovery Using Deep Generative Models.

Designing a new drug is a lengthy and expensive process. As the space of potential molecules is very large ( Polishchuk , P. G. ; Madzhidov , T. I. ; ...

Knowledge-Based Planning for Identifying High-Risk Stereotactic Ablative Radiation Therapy Treatment Plans for Lung Tumors Larger Than 5 cm.

PURPOSE: Stereotactic ablative body radiation therapy (SABR) for lung tumors ≥5 cm can be associated with more toxicity than that for smaller tumors. ...

Identifying epidermal growth factor receptor mutation status in patients with lung adenocarcinoma by three-dimensional convolutional neural networks.

OBJECTIVE:: Genetic phenotype plays a central role in making treatment decisions of lung adenocarcinoma, especially the tyrosine-kinase-inhibitors-sen...

FissureNet: A Deep Learning Approach For Pulmonary Fissure Detection in CT Images.

Pulmonary fissure detection in computed tomography (CT) is a critical component for automatic lobar segmentation. The majority of fissure detection me...