Pulmonology

Prediction of visceral pleural invasion of clinical stage I lung adenocarcinoma using thoracoscopic images and deep learning.

PURPOSE: To develop deep learning models using thoracoscopic images to identify visceral pleural invasion (VPI) in patients with clinical stage I lung adenocarcinoma, and to verify if these models can be applied clinically.

Prognostication of lung adenocarcinomas using CT-based deep learning of morphological and histopathological features: a retrospective dual-institutional study.

OBJECTIVES: To develop and validate CT-based deep learning (DL) models that learn morphological and histopathological features for lung adenocarcinoma prognostication, and to compare them with a previously developed DL discrete-time survival model.

An event-triggered collaborative neurodynamic approach to distributed global optimization.

In this paper, we propose an event-triggered collaborative neurodynamic approach to distributed global optimization in the presence of nonconvexity. W...

Risk factors of early mortality in COVID-19 patients in Indonesia: A retrospective cohort study in a provincial referral hospital of Aceh.

Some of coronavirus disease 2019 (COVID-19) patients died after being hospitalized and early mortality is a matter of concern during the pandemic; the...

Deep learning-based sleep stage classification with cardiorespiratory and body movement activities in individuals with suspected sleep disorders.

Deep learning methods have gained significant attention in sleep science. This study aimed to assess the performance of a deep learning-based sleep st...

Pressure support ventilation in intensive care patients receiving prolonged invasive ventilation.

To our knowledge, the use and management of pressure support ventilation (PSV) in patients receiving prolonged (≥ 7 days) invasive mechanical ventila...

Rapid 500 mL albumin bolus versus rapid 200 mL bolus followed by slower continuous infusion in post-cardiac surgery patients: a pilot before-and-after study.

To evaluate the haemodynamic effects of rapid fluid bolus therapy (FBT) (500 mL of 4% albumin over several minutes) versus combined FBT (rapid 200 mL...

Temperature and haemodynamic effects of a 100 mL bolus of 20% albumin at room versus body temperature in cardiac surgery patients.

To study the temperature and haemodynamic effects of room versus body temperature 20% albumin fluid bolus therapy (FBT). Single-centre, prospective,...

Application of artificial intelligence in quantifying lung deposition dose of black carbon in people with exposure to ambient combustion particles.

BACKGROUND: Understanding lung deposition dose of black carbon is critical to fully reconcile epidemiological evidence of combustion particles induced...

Development of a novel artificial intelligence algorithm to detect pulmonary nodules on chest radiography.

BACKGROUND: In this study, we aimed to develop a novel artificial intelligence (AI) algorithm to support pulmonary nodule detection, which will enable...

Blue-emitting SiO-coated Si-doped ZnSeS quantum dots conjugated aptamer-molecular beacon as an electrochemical and metal-enhanced fluorescence biosensor for SARS-CoV-2 spike protein.

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) which was first reported in early January 2020, continues to devastate th...

Influenza Epidemic Trend Surveillance and Prediction Based on Search Engine Data: Deep Learning Model Study.

BACKGROUND: Influenza outbreaks pose a significant threat to global public health. Traditional surveillance systems and simple algorithms often strugg...

Developing a risk prediction tool for lung cancer in Kent and Medway, England: cohort study using linked data.

BACKGROUND: Lung cancer has the poorest survival due to late diagnosis and there is no universal screening. Hence, early detection is crucial. Our obj...

Computer-aided diagnosis of chest X-ray for COVID-19 diagnosis in external validation study by radiologists with and without deep learning system.

To evaluate the diagnostic performance of our deep learning (DL) model of COVID-19 and investigate whether the diagnostic performance of radiologists ...

Application of multiple-finding segmentation utilizing Mask R-CNN-based deep learning in a rat model of drug-induced liver injury.

Drug-induced liver injury (DILI) presents significant diagnostic challenges, and recently artificial intelligence-based deep learning technology has b...

Batch normalization followed by merging is powerful for phenotype prediction integrating multiple heterogeneous studies.

Heterogeneity in different genomic studies compromises the performance of machine learning models in cross-study phenotype predictions. Overcoming het...

Comparison of clinical efficacy of da Vinci robot-assisted lung cancer surgery with two-, three- and four-hole approaches.

Orifice reduction strategies for da Vinci robotic surgery have been a hot topic of research in recent years. We retrospectively analyzed the periopera...

A Deep Learning-Based Radiomic Classifier for Usual Interstitial Pneumonia.

BACKGROUND: Because chest CT scan has largely supplanted surgical lung biopsy for diagnosing most cases of interstitial lung disease (ILD), tools to s...

Continuous visualization and validation of pain in critically ill patients using artificial intelligence: a retrospective observational study.

Machine learning tools have demonstrated viability in visualizing pain accurately using vital sign data; however, it remains uncertain whether incorpo...

Localization and phenotyping of tuberculosis bacteria using a combination of deep learning and SVMs.

Successful treatment of pulmonary tuberculosis (TB) depends on early diagnosis and careful monitoring of treatment response. Identification of acid-fa...