Pulmonology

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

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The utilisation of convolutional neural networks in detecting pulmonary nodules: a review.

Lung cancer is one of the leading causes of cancer-related fatality in the world. Patients display f...

Adaptive multinomial regression with overlapping groups for multi-class classification of lung cancer.

Multi-class classification has attracted much attention in cancer diagnosis and treatment and many m...

Peripheral bronchial identification on chest CT using unsupervised machine learning.

PURPOSE: To automatically identify small- to medium-diameter bronchial segments distributed througho...

A Nasal Brush-based Classifier of Asthma Identified by Machine Learning Analysis of Nasal RNA Sequence Data.

Asthma is a common, under-diagnosed disease affecting all ages. We sought to identify a nasal brush-...

The comparison of pleural fluid TNF-α levels in tuberculous and nontuberculous pleural effusion.

BACKGROUND: Tuberculous pleural effusion is the manifestation of Mycobacterium tuberculosis infectio...

Inhalable Fucoidan Microparticles Combining Two Antitubercular Drugs with Potential Application in Pulmonary Tuberculosis Therapy.

The pulmonary delivery of antitubercular drugs is a promising approach to treat lung tuberculosis. T...

Modeling asynchronous event sequences with RNNs.

Sequences of events have often been modeled with computational techniques, but typical preprocessing...

Profiling Lung Cancer Patients Using Electronic Health Records.

If Electronic Health Records contain a large amount of information about the patient's condition and...

Evolutionary image simplification for lung nodule classification with convolutional neural networks.

PURPOSE: Understanding decisions of deep learning techniques is important. Especially in the medical...

Prediction of radiographic abnormalities by the use of bag-of-features and convolutional neural networks.

This study evaluated the feasibility of bag-of-features (BOF) and convolutional neural networks (CNN...

Chronic obstructive lung disease "expert system": validation of a predictive tool for assisting diagnosis.

PURPOSE: The purposes of this study were development and validation of an expert system (ES) aimed a...

Classification of Sputum Sounds Using Artificial Neural Network and Wavelet Transform.

Sputum sounds are biological signals used to evaluate the condition of sputum deposition in a respir...

Screening for active pulmonary tuberculosis: Development and applicability of artificial neural network models.

Tuberculosis (TB) remains a significant public health challenge, motivated by the diversity of healt...

Segmentation of histological images and fibrosis identification with a convolutional neural network.

Segmentation of histological images is one of the most crucial tasks for many biomedical analyses in...

Deep learning for staging liver fibrosis on CT: a pilot study.

OBJECTIVES: To investigate whether liver fibrosis can be staged by deep learning techniques based on...

Harnessing the evolutionary information on oxygen binding proteins through Support Vector Machines based modules.

OBJECTIVES: The arrival of free oxygen on the globe, aerobic life is becoming possible. However, it ...

Ultra-protective mechanical ventilation without extra-corporeal carbon dioxide removal for acute respiratory distress syndrome.

BACKGROUND: Tidal hyperinflation can still occur with mechanical ventilation using low tidal volume ...

Using machine learning to identify patterns of lifetime health problems in decedents with autism spectrum disorder.

Very little is known about the health problems experienced by individuals with autism spectrum disor...

Pulmonary Artery-Vein Classification in CT Images Using Deep Learning.

Recent studies show that pulmonary vascular diseases may specifically affect arteries or veins throu...

Lung sounds classification using convolutional neural networks.

Lung sounds convey relevant information related to pulmonary disorders, and to evaluate patients wit...

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