[95% CI, 10.2–13.3%], p < 0.001 for radiologists).ConclusionsAI algorithm can enhance the performance of readers for the detection of lung cancers on chest radiographs when used as second reader.Key Points Reader study in the NLST dataset shows that AI algorithm had sensitivity benefit for ...
In the other large randomized, prospective study on LC screening, the NELSON screening trial,13 spirometry was performed in 1108 participants with only 437 having OLD, a much smaller dataset which will likely be underpowered to determine if LDCT can decrease LC mortality in those subjects. ...
Lung cancerBackground: A deep learning system for lung nodule detection from low dose CT scans was trained on a public database. This study aims to evaluate its performance on an independent screening dataset and specifically its ability to detect malignant lesions one year prior to diagnosis....
Using a dataset of over twelve thousand biopsy proven cases of lung cancer, the trained classification model achieved an accuracy of 97.15% with a PPV of 99.88% and a NPV of 94.81%, beating models such as Inception-V3 and ResNet-152 while simultaneously reducing the number of parameters a ...