Pulmonology

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

This study aimed to assess the image quality and accuracy of respiratory-gated real-time two-dimensional (2D) cine incorporating deep learning reconstruction (DLR) for the quantification of biventricular volumes and function compared with those of the standard reference, that is, breath-hold 2D balanced steady-state free precession (bSSFP) cine, in an adult population. Twenty-four patients (15 men...

Large-scale prediction of stream water quality using an interpretable deep learning approach.

Deep learning methods, which have strong capabilities for mapping highly nonlinear relationships with acceptable calculation speed, have been increasingly applied for water quality prediction in recent studies. However, it is argued that the practicality of deep learning methods is limited due to the lack of physical mechanics to explain the prediction results of water quality changes. A knowledge...

Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.

Background Patients presenting to the emergency department (ED) with acute chest pain (ACP) syndrome undergo additional testing to exclude acute coron...

Deep learning classification of active tuberculosis lung zones wise manifestations using chest X-rays: a multi label approach.

Chest X-rays are the most economically viable diagnostic imaging test for active pulmonary tuberculosis screening despite the high sensitivity and low...

Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography.

PURPOSE: Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that ...

Machine Learning Models for the Automatic Detection of Exercise Thresholds in Cardiopulmonary Exercising Tests: From Regression to Generation to Explanation.

The cardiopulmonary exercise test (CPET) constitutes a gold standard for the assessment of an individual's cardiovascular fitness. A trend is emerging...

Current Advances in Computational Lung Ultrasound Imaging: A Review.

In the field of biomedical imaging, ultrasonography has become common practice, and used as an important auxiliary diagnostic tool with unique advanta...

Coronavirus covid-19 detection by means of explainable deep learning.

The coronavirus is caused by the infection of the SARS-CoV-2 virus: it represents a complex and new condition, considering that until the end of Decem...

Robot-assisted complex urinary tract reconstruction using intestinal segments: redefining the paradigm.

Complex urinary tract reconstruction has significantly advanced with the increasing use of robot-assisted procedures. Robotic surgery aims to achieve ...

Predicting N2 lymph node metastasis in presurgical stage I-II non-small cell lung cancer using multiview radiomics and deep learning method.

BACKGROUND: Accurate diagnosis of N2 lymph node status of the resectable stage I-II non-small cell lung cancer (NSCLC) before surgery is crucial, whil...

Hospital crowdedness evaluation and in-hospital resource allocation based on image recognition technology.

How to allocate the existing medical resources reasonably, alleviate hospital congestion and improve the patient experience are problems faced by all ...

Compensation for respiratory motion-induced signal loss and phase corruption in free-breathing self-navigated cine DENSE using deep learning.

PURPOSE: To introduce a model that describes the effects of rigid translation due to respiratory motion in displacement encoding with stimulated echoe...

Haemodynamic and respiratory perioperative outcomes for open versus robot-assisted radical cystectomy: A double-blinded, randomised trial.

BACKGROUND: The clinical impact of prolonged steep Trendelenburg position and CO pneumoperitoneum during robot-assisted radical cystectomy (RC) on int...

Lung Sound Recognition Method Based on Wavelet Feature Enhancement and Time-Frequency Synchronous Modeling.

Lung diseases are serious threats to human health and life, therefore, an accurate diagnosis of lung diseases is significant. The use of artificial in...

Development and Validation of a Deep Learning-Based Synthetic Bone-Suppressed Model for Pulmonary Nodule Detection in Chest Radiographs.

IMPORTANCE: Dual-energy chest radiography exhibits better sensitivity than single-energy chest radiography, partly due to its ability to remove overly...

Case of robot-assisted salvage surgery for esophageal cancer with a mediastinal fistula after definitive chemoradiotherapy.

Salvage surgery for esophageal cancer after definitive chemoradiotherapy (dCRT) is effective, but it is associated with a high rate of perioperative c...

LDDNet: A Deep Learning Framework for the Diagnosis of Infectious Lung Diseases.

This paper proposes a new deep learning (DL) framework for the analysis of lung diseases, including COVID-19 and pneumonia, from chest CT scans and X-...

Prognostic significance of pulmonary arterial wedge pressure estimated by deep learning in acute heart failure.

AIMS: Acute decompensated heart failure (ADHF) presents with pulmonary congestion, which is caused by an increased pulmonary arterial wedge pressure (...

TNN: Tree Neural Network for Airway Anatomical Labeling.

Detailed anatomical labeling of bronchial trees extracted from CT images can be used as fine-grained maps for intra-operative navigation. To cater to ...

A Hybrid Model for Coronavirus Disease 2019 Forecasting Based on Ensemble Empirical Mode Decomposition and Deep Learning.

The novel coronavirus pneumonia that began to spread in 2019 is still raging and has placed a burden on medical systems and governments in various cou...