Pulmonology

Machine learning for syndromic surveillance using veterinary necropsy reports.

The use of natural language data for animal population surveillance represents a valuable opportunity to gather information about potential disease outbreaks, emerging zoonotic diseases, or bioterrorism threats. In this study, we evaluate machine learning methods for conducting syndromic surveillance using free-text veterinary necropsy reports. We train a system to detect if a necropsy report from...

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 antiretroviral therapy (ART). Monocytes and macrophages have been implicated in the pathogenesis of fibrosis, facilitated by chemokine receptor interactions. We assessed systemic fibrotic biomarkers (transforming growth factor beta-1 [TGF-β1], thrombospondin-1 [TSP-1], C-terminal pro-peptide of collagen ...

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. The diagnosis of COPD is generally based on the ...

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 intensive care unit (ICU) due to unexpected clinical...

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-dimensional computed tomography (4DCT) ventilation ima...

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 (3D) positions of lung tumors from continuously a...

The Emerging Role of Radiomics in COPD and Lung Cancer.

Medical imaging plays a key role in evaluating and monitoring lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. The ...

Determination of causes of death via spectrochemical analysis of forensic autopsies-based pulmonary edema fluid samples with deep learning algorithm.

This study investigated whether infrared spectroscopy combined with a deep learning algorithm could be a useful tool for determining causes of death b...

Untethered Soft Robotics with Fully Integrated Wireless Sensing and Actuating Systems for Somatosensory and Respiratory Functions.

There has been a great deal of interest in designing soft robots that can mimic a human system with haptic and proprioceptive functions. There is now ...

Investigating the use of data-driven artificial intelligence in computerised decision support systems for health and social care: A systematic review.

There is growing interest in the potential of artificial intelligence to support decision-making in health and social care settings. There is, however...

A deep convolutional neural network architecture for interstitial lung disease pattern classification.

Interstitial lung disease (ILD) refers to a group of various abnormal inflammations of lung tissues and early diagnosis of these disease patterns is c...

Image Quality and Lesion Detection on Deep Learning Reconstruction and Iterative Reconstruction of Submillisievert Chest and Abdominal CT.

The objective of this study was to compare image quality and clinically significant lesion detection on deep learning reconstruction (DLR) and iterat...

Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound im...

Portable Detection of Apnea and Hypopnea Events Using Bio-Impedance of the Chest and Deep Learning.

Sleep apnea is one of the most common sleep-related breathing disorders. It is diagnosed through an overnight sleep study in a specialized sleep clini...

Scalogram based prediction model for respiratory disorders using optimized convolutional neural networks.

Auscultation of the lung is a conventional technique used for diagnosing chronic obstructive pulmonary diseases (COPDs) and lower respiratory infectio...

Liver tissue classification of en face images by fractal dimension-based support vector machine.

Full-field optical coherence tomography (FF-OCT) has been reported with its label-free subcellular imaging performance. To realize quantitive cancer d...

Automatic lesion segmentation and classification of hepatic echinococcosis using a multiscale-feature convolutional neural network.

Hepatic echinococcosis (HE) is a life-threatening liver disease caused by parasites that requires a precise diagnosis and proper treatments. To assess...

Classification of Interstitial Lung Abnormality Patterns with an Ensemble of Deep Convolutional Neural Networks.

Subtle interstitial changes in the lung parenchyma of smokers, known as Interstitial Lung Abnormalities (ILA), have been associated with clinical outc...

Digging Deeper to Save the Old Anti-tuberculosis Target: D-Alanine-D-Alanine Ligase With a Novel Inhibitor, IMB-0283.

The emergence of drug-resistant (Mtb) has hampered treatments for tuberculosis, which consequently now require novel agents to overcome such drug res...

Deep learning, computer-aided radiography reading for tuberculosis: a diagnostic accuracy study from a tertiary hospital in India.

In general, chest radiographs (CXR) have high sensitivity and moderate specificity for active pulmonary tuberculosis (PTB) screening when interpreted ...