Purpose To develop and validate a deep learning-based automatic detection algorithm (DLAD) for malignant pulmonary nodules on chest radiographs and to compare its performance with physicians including thoracic radiologists. Materials and Methods For ...
Lung cancer screening aims to detect small pulmonary nodules and decrease the mortality rate of those affected. However, studies from large-scale clinical trials of lung cancer screening have shown that the false-positive rate is high and positive pr...
Journal of computer assisted tomography
May 13, 2025
OBJECTIVE: To investigate the performance of Dual-AI Deep Learning Platform in detecting unreported pulmonary nodules that are 6 mm or greater, comprising computer-vision (CV) algorithm to detect pulmonary nodules, with positive results filtered by n...
PURPOSE: To evaluate the feasibility and utility of deep learning-based computer-aided diagnosis (DL-CAD) for the detection of pulmonary nodules on coronary artery calcium (CAC)-scoring computed tomography (CT).
Purpose To evaluate the performance of eight lung cancer prediction models on patient cohorts with screening-detected, incidentally detected, and bronchoscopically biopsied pulmonary nodules. Materials and Methods This study retrospectively evaluated...
BACKGROUND: Early and timely detection of pulmonary nodules and initiation treatment can substantially improve the survival rate of lung carcinoma. However, current detection methods based on convolutional neural networks (CNNs) cannot easily detect ...
The aim of our study was to evaluate the specific performance of an artificial intelligence (AI) algorithm for lung nodule detection in chest radiography for a larger number of nodules of different sizes and densities using a standardized phantom app...
BACKGROUND: Correctly distinguishing between benign and malignant pulmonary nodules can avoid unnecessary invasive procedures. This study aimed to construct a deep learning radiomics clinical nomogram (DLRCN) for predicting malignancy of pulmonary no...
BACKGROUND: Clinical utility data on pulmonary nodule (PN) risk stratification biomarkers are lacking. We aimed to determine the incremental predictive value and clinical utility of using an artificial intelligence (AI) radiomics-based computer-aided...
Zhonghua jie he he hu xi za zhi = Zhonghua jiehe he huxi zazhi = Chinese journal of tuberculosis and respiratory diseases
Jun 12, 2024
Lung cancer, which accounts for about 18% of all cancer-related deaths worldwide, has a dismal 5-year survival rate of less than 20%. Survival rates for early-stage lung cancers (stages IA1, IA2, IA3, and IB, according to the TNM staging system) are ...