Artificial intelligence (AI) is gradually changing medical practice. With recent progress in
digitized data acquisition, machine learning and computing infrastructure, AI applications …

Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …

Machine learning is used increasingly in clinical care to improve diagnosis, treatment
selection, and health system efficiency. Because machine-learning models learn from …

The interpretation of deep learning models is a challenge due to their size, complexity, and
often opaque internal state. In addition, many systems, such as image classifiers, operate on …

Traditionally, medical discoveries are made by observing associations, making hypotheses
from them and then designing and running experiments to test the hypotheses. However …

Deep learning applications in ophthalmology : Current Opinion in Ophthalmology Deep learning
applications in ophthalmology : Current Opinion in Ophthalmology Log in or Register Subscribe …

Rising prevalence of diabetes worldwide has necessitated the implementation of population-
based diabetic retinopathy (DR) screening programs that can perform retinal imaging and …

Artificial intelligence is a general term that means to accomplish a task mainly by a
computer, with the least human beings participation, and it is widely accepted as the …

The Machine Recognition of Crystallization Outcomes (MARCO) initiative has assembled
roughly half a million annotated images of macromolecular crystallization experiments from …

Crowdsourced classification of data typically assumes that objects can be unambiguously
classified into categories. In practice, many classification tasks are ambiguous due to …