Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...
Objectives Parametric response mapping (PRM) enables the evaluation of small airway disease (SAD) at the voxel level, but requires both inspiratory and expiratory chest CT scans. We hypothesize that deep learning PRM from inspiratory chest CT scans can eff ...
Robustness of medical image classification models is limited by its exposure to the candidate disease classes. Generalized zero shot learning (GZSL) aims at correctly predicting seen and unseen classes and most current GZSL approaches have focused on the s ...
Objectives To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. ...
ObjectiveTo construct a new pulmonary nodule diagnostic model with high diagnostic efficiency, non-invasive and simple to measure. MethodsThis study included 424 patients with radioactive pulmonary nodules who underwent preoperative 7-autoantibody (7-AAB) ...
Point-of-care ultrasound (POCUS) is an increasingly accessible skill, allowing for the decentralization of its use to nonspecialist healthcare workers to guide routine clinical decision-making. The advent of ultrasound-on-a-chip has transformed the technol ...
A method of analyzing human pulmonary X-rays using a few software procedures to process the images will be presented. Photographs of the lungs were investigated and images of the arteries were illustrated, successfully extracting the shadows due to the rib ...
Background: Chronic obstructive pulmonary disease (COPD) is one of the most common disorders in the world. COPD is characterized by airflow obstruction, which is not fully reversible. Patients usually experience breathing-related symptoms with periods of a ...
Background Malignant pleural mesothelioma (MPM) is a rare and aggressive cancer related to asbestos exposure. The tumor microenvironment content, particularly the presence of macrophages, was described as crucial for the development of the disease. This wo ...
Training robust deep learning (DL) systems for disease detection from medical images is challenging due to limited images covering different disease types and severity. The problem is especially acute, where there is a severe class imbalance. We propose an ...
