Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …

Deep learning (DL) has the potential to transform medical diagnostics. However, the
diagnostic accuracy of DL is uncertain. Our aim was to evaluate the diagnostic accuracy of …

Background Deep learning offers considerable promise for medical diagnostics. We aimed
to evaluate the diagnostic accuracy of deep learning algorithms versus health-care …

One of the most common and deadly diseases in the world is lung cancer. Only early
identification of lung cancer can increase a patient's probability of survival. A frequently used …

Deep learning, for image data processing, has been widely used to solve a variety of
problems related to medical practices. However, researchers are constantly struggling to …

Simple Summary Lung cancer screening has been shown to help reduce mortality in
selected populations of smokers; however, performing screening programs at a larger scale …

Background Outside a screening program, early-stage lung cancer is generally diagnosed
after the detection of incidental nodules in clinically ordered chest CT scans. Despite the …

Lung cancer has been one of the most prevalent disease in recent years. According to the
research of this field, more than 200,000 cases are identified each year in the US …

Deep learning methods have huge success in task specific feature representation. Transfer
learning algorithms are very much effective when large training data is scarce. It has been …

Background Lung cancer is the principal cause of cancer-related deaths worldwide. Early
detection of lung cancer with screening is indispensable to reduce the high morbidity and …