Pulmonology

An expert-based system to predict population survival rate from health data.

Timely detection and understanding of causes for population decline are essential for effective wild...

A multicenter evaluation of a deep learning software (LungQuant) for lung parenchyma characterization in COVID-19 pneumonia.

BACKGROUND: The role of computed tomography (CT) in the diagnosis and characterization of coronaviru...

Deep learning approach for prediction and classification of potable water.

Potable water, commonly known as drinking water, refers to water that is safe to drink and does not ...

Coupling analysis of heart rate variability and cortical arousal using a deep learning algorithm.

Frequent cortical arousal is associated with cardiovascular dysfunction among people with sleep-diso...

Radiologist Worklist Reprioritization Using Artificial Intelligence: Impact on Report Turnaround Times for CTPA Examinations Positive for Acute Pulmonary Embolism.

In patients with acute pulmonary embolism (PE), timely intervention (e.g., initiation of anticoagul...

A systematic review and repeatability study on the use of deep learning for classifying and detecting tuberculosis bacilli in microscopic images.

Tuberculosis (TB) is among the leading causes of death worldwide from a single infectious agent. Thi...

Using artificial intelligence to enhance the diagnostic accuracy of the 12-lead electrocardiogram in patients with suspected acute pulmonary embolism - Can you teach an old dog new tricks?

A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI.

BACKGROUND: Hyperpolarized gas MRI is a functional lung imaging modality capable of visualizing regi...

Leptin levels in childhood tuberculosis and its correlation with body mass index, IFN-γ, and TNF-α in an Indonesian population.

BACKGROUND: Leptin plays a key role in the regulation of energy and inflammation in tuberculosis (TB...

Benchmark methodological approach for the application of artificial intelligence to lung ultrasound data from COVID-19 patients: From frame to prognostic-level.

Automated ultrasound imaging assessment of the effect of CoronaVirus disease 2019 (COVID-19) on lung...

Artificial intelligence-based diagnosis of acute pulmonary embolism: Development of a machine learning model using 12-lead electrocardiogram.

INTRODUCTION: Pulmonary embolism (PE) is a life-threatening condition, in which diagnostic uncertain...

Impact on the ability of healthcare professionals to correctly identify patient-ventilator asynchronies of the simultaneous visualization of estimated muscle pressure curves on the ventilator display: a randomized study (P study).

BACKGROUND: Patient-ventilator asynchronies are usually detected by visual inspection of ventilator ...

Effect of Deep Learning Reconstruction on Respiratory-triggered T2-weighted MR Imaging of the Liver: A Comparison between the Single-shot Fast Spin-echo and Fast Spin-echo Sequences.

PURPOSE: To compare the effects of deep learning reconstruction (DLR) on respiratory-triggered T2-we...

Enhancing Multi-disease Diagnosis of Chest X-rays with Advanced Deep-learning Networks in Real-world Data.

The current artificial intelligence (AI) models are still insufficient in multi-disease diagnosis fo...

Effects of robot-assisted gait training on cardiopulmonary function and lower extremity strength in individuals with spinal cord injury: A systematic review and meta-analysis.

CONTEXT: Robot-assisted gait training (RAGT) has been increasingly adopted in many rehabilitation fa...

Utilization of Deep Convolutional Neural Networks for Accurate Chest X-Ray Diagnosis and Disease Detection.

Chest radiography is a widely used diagnostic imaging procedure in medical practice, which involves ...

Deep learning-based fast volumetric imaging using kV and MV projection images for lung cancer radiotherapy: A feasibility study.

PURPOSE: The long acquisition time of CBCT discourages repeat verification imaging, therefore increa...

Convolutional neural network-based automated maxillary alveolar bone segmentation on cone-beam computed tomography images.

OBJECTIVES: To develop and assess the performance of a novel artificial intelligence (AI)-driven con...

Memory efficient model based deep learning reconstructions for high spatial resolution 3D non-cartesian acquisitions.

. Model based deep learning (MBDL) has been challenging to apply to the reconstruction of 3D non-Car...

The value of artificial intelligence in the diagnosis of lung cancer: A systematic review and meta-analysis.

Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Curre...

Artificial intelligence based virtual screening study for competitive and allosteric inhibitors of the SARS-CoV-2 main protease.

SARS-CoV-2 is a highly contagious and dangerous coronavirus that first appeared in late 2019 causing...