Pulmonology

Reliability of respiratory-gated real-time two-dimensional cine incorporating deep learning reconstruction for the assessment of ventricular function in an adult population; a common mistake.

Reliability (repeatability or agreement) is assessed by different statistical tests including Pearson r or Spearman rho which is one of the common mistakes in reliability analysis. Pearson r or Spearman rho correlation coefficient only assesses the linearity between two continuous variables. Any shift in the regression line's location or scale, which leads to non-reliability, cannot be detected by...

Dynamic risk assessment of hospital oxygen supply system by HAZOP and intuitionistic fuzzy.

Events such as oxygen leakage in the oxygen generation systems can have severe consequences, such as fire and explosion. In addition, the disruption in the oxygenation systems can lead to a threat to patients' lives. Thus, this study aimed to identify the significant deviations in the oxygen supply system as critical equipment at hospitals based on the Hazard and Operability (HAZOP) method. Despit...

Transvesical Percutaneous Access Allows for Epidural Anesthesia Without Mechanical Ventilation in Single-Port Robotic Radical and Simple Prostatectomy.

OBJECTIVES: To determine the feasibility of epidural anesthesia in patients undergoing transvesical single-port (SP) robotic simple and radical prosta...

Dyspnea Severity Assessment Based on Vocalization Behavior with Deep Learning on the Telephone.

In this paper, a system to assess dyspnea with the mMRC scale, on the phone, via deep learning, is proposed. The method is based on modeling the spont...

CoO/CoFeO Hollow Nanocube Multifunctional Nanozyme with Oxygen Vacancies for Deep-Learning-Assisted Smartphone Biosensing and Organic Pollutant Degradation.

Although the application of nanozymes has been widely studied, it is still a huge challenge to develop highly active and multifunctional nanozyme cata...

Deep learning ensemble 2D CNN approach towards the detection of lung cancer.

In recent times, deep learning has emerged as a great resource to help research in medical sciences. A lot of work has been done with the help of comp...

Fractional Dynamics Foster Deep Learning of COPD Stage Prediction.

Chronic obstructive pulmonary disease (COPD) is one of the leading causes of death worldwide. Current COPD diagnosis (i.e., spirometry) could be unrel...

Enhancing Nodule Biopsy Through Technology Integration.

Technology in navigating to peripheral pulmonary nodules has improved in recent years. The recent integration of a robotic platform using shape-sensin...

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton ( H)-MRI lung segm...

Quantification of Comfort for the Development of Binding Parts in a Standing Rehabilitation Robot.

Human-machine interfaces (HMI) refer to the physical interaction between a user and rehabilitation robots. A persisting excessive load leads to soft t...

Surrogate Modelling for Oxygen Uptake Prediction Using LSTM Neural Network.

Oxygen uptake (V˙O2) is an important metric in any exercise test including walking and running. It can be measured using portable spirometers or metab...

Deep-learning algorithm to detect fibrosing interstitial lung disease on chest radiographs.

BACKGROUND: Antifibrotic therapies are available to treat chronic fibrosing interstitial lung diseases (CF-ILDs), including idiopathic pulmonary fibro...

Defining the learning curve of robotic portal segmentectomy in small pulmonary lesions: a prospective observational study.

Although robotic segmentectomy has been applied for the treatment of small pulmonary lesions for many years, studies on the learning curve of robotic ...

Deep Learning-based Approach to Predict Pulmonary Function at Chest CT.

Background Low-dose chest CT screening is recommended for smokers with the potential for lung function abnormality, but its role in predicting lung fu...

Monitoring the respiratory behavior of multiple cows based on computer vision and deep learning.

Automatic respiration monitoring of dairy cows in modern farming not only helps to reduce manual labor but also increases the automation of health ass...

Sooty Tern Optimization Algorithm-Based Deep Learning Model for Diagnosing NSCLC Tumours.

Lung cancer is one of the most common causes of cancer deaths in the modern world. Screening of lung nodules is essential for early recognition to fac...

LGEANet: LSTM-global temporal convolution-external attention network for respiratory motion prediction.

PURPOSE: To develop a deep learning network that treats the three-dimensional respiratory motion signals as a whole and considers the inter-dimensiona...

Deep-Learning Model for Influenza Prediction From Multisource Heterogeneous Data in a Megacity: Model Development and Evaluation.

BACKGROUND: In megacities, there is an urgent need to establish more sensitive forecasting and early warning methods for acute respiratory infectious ...

Comparison of Short-Term Outcomes Between Robot-Assisted and Video-Assisted Segmentectomy for Small Pulmonary Nodules: A Propensity Score-Matching Study.

BACKGROUND: Our study aimed to compare the short-term outcomes between robot-assisted segmentectomy (RAS) and video-assisted segmentectomy (VAS) for s...

ASO Author Reflections: Which Technique is Superior for Segmentectomy of Small Pulmonary Nodules: Robot-Assisted or Video-Assisted?