Background Transfer learning (TL) with convolutional neural networks aims to improve
performances on a new task by leveraging the knowledge of similar tasks learned in …

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 …

Glaucoma is one of the leading causes of irreversible but preventable blindness in working
age populations. Color fundus photography (CFP) is the most cost-effective imaging …

Objective Employing transfer learning (TL) with convolutional neural networks (CNNs), well-
trained on non-medical ImageNet dataset, has shown promising results for medical image …

Artificial intelligence is widely applied to automate Diabetic retinopathy diagnosis. Diabetes-
related retinal vascular disease is one of the world's most common leading causes of …

Glaucoma is an eye disease initiated due to excessive intraocular pressure inside it and
caused complete sightlessness at its progressed stage. Whereas timely glaucoma screening …

Glaucoma is a major global cause of blindness. As the symptoms of glaucoma appear, when
the disease reaches an advanced stage, proper screening of glaucoma in the early stages is …

With the utilization of deep learning approaches, the key factors for a successful application
are sufficient datasets with reliable ground truth, which are generally not easy to obtain …

A method for detecting glaucoma based only on optical coherence tomography (OCT) is of
potential value for routine clinical decisions, for inclusion criteria for research studies and …