(AI) in thoracic imaging, particularly in the interpretation of chest radiographs. The use of
deep learning to detect pulmonary tuberculosis on chest radiographs has demonstrated …

Recently, interest and advances in artificial intelligence (AI) including deep learning for
medical images have surged. As imaging plays a major role in the assessment of pulmonary …

Since the advent of deep learning, a new stage of the digital revolution is underway. In the
medical field, radiology is particularly well suited to this new transition due to the digitization …

Deep learning is a genre of machine learning that allows computational models to learn
representations of data with multiple levels of abstraction using numerous processing layers …

Background Compared to classical computer-aided analysis, deep learning and in particular
deep convolutional neural network demonstrates breakthrough performance in many of the …

Artificial intelligence is a hot topic in medical imaging. The development of deep learning
methods and in particular the use of convolutional neural networks (CNNs), have led to …

Kiran Vaidhya Venkadesh, PhD, is a postdoctoral researcher at Radboud University Medical
Center in Nijmegen, the Netherlands. He is part of the Diagnostic Image Analysis Group …

Background Deep learning (DL) based solutions have been proposed for interpretation of
several imaging modalities including radiography, CT, and MR. For chest radiographs, DL …

Relevance and penetration of machine learning in clinical practice is a recent phenomenon
with multiple applications being currently under development. Deep learning—and …

Purpose: Manual interpretation of chest radiographs is a challenging task and is prone to
errors. An automated system capable of categorizing chest radiographs based on the …