Latest AI and machine learning research in pulmonology for healthcare professionals.
Radiotherapy requires the target area and the organs at risk to be contoured on the CT image of the patient. During the process of organs-at-Risk (OAR) of the chest and abdomen, the doctor needs to contour at each CT image. The delineations of large and varied shapes are time-consuming and laborious. This study aims to evaluate the results of two automatic contouring softwares on OARs definition o...
The study aimed to explore the diagnostic value of computed tomography (CT) images based on cavity convolution U-Net algorithm for patients with severe pulmonary infection. A new lung CT image segmentation algorithm (U-Net+ deep convolution (DC)) was proposed based on U-Net network and compared with convolutional neural network (CNN) algorithm. Then, it was applied to CT image diagnosis of 100 pat...
AIMS: Clinical scoring systems for pulmonary embolism (PE) screening have low specificity and contribute to computed tomography pulmonary angiogram (C...
Bovine respiratory disease (BRD) is a multifactorial disease involving complex host immune interactions shaped by pathogenic agents and environmental ...
Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including . We built a de...
OBJECTIVE: To evaluate the performance of a deep learning-based computer-aided detection (DL-CAD) system in a Chinese low-dose CT (LDCT) lung cancer s...
BACKGROUND: Rapid intraoperative diagnosis for unconfirmed pulmonary tumor is extremely important for determining the optimal surgical procedure (lobe...
The early detection of pulmonary nodules using computer-aided diagnosis (CAD) systems is very essential in reducing mortality rates of lung cancer. In...
The full-iterative model reconstruction generates ultra-high-resolution computed tomography (U-HRCT) images comprising a 1024 × 1024 matrix and 0.25 m...
BACKGROUND: With the rapid spread of COVID-19 worldwide, quick screening for possible COVID-19 patients has become the focus of international research...
To discuss the application method and effect of COPD patients in deep learning in intelligent monitoring, two groups were used under a reasonable sele...
OBJECTIVE: High tidal volume ventilation is associated with ventilator-induced lung injury. Early introduction of lung protective ventilation improves...
Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based o...
Soft robots can provide advantages for medical interventions given their low cost and their ability to change shape and safely apply forces to tissue....
AIMS: Immunohistochemical programmed death-ligand 1 (PD-L1) staining to predict responsiveness to immunotherapy in patients with advanced non-small ce...
PURPOSE: Adaptive proton therapy (APT) of lung cancer patients requires frequent volumetric imaging of diagnostic quality. Cone-beam CT (CBCT) can pro...
PURPOSE: A growing number of studies have examined whether Artificial Intelligence (AI) systems can support imaging-based diagnosis of COVID-19-caused...
Fast recovery, high sensitivity, high selectivity, and room temperature (RT) sensing characteristics of NO gas sensors are essential for environmental...
In order to evaluate the postoperative nursing effect of artificial intelligence robot-assisted thoracic surgery, this study proposed the Da Vinci rob...
COVID-19 is an infectious disease, which has adversely affected public health and the economy across the world. On account of the highly infectious na...