
AIs detect diabetic eye disease inconsistently
Although some artificial intelligence software tested reasonably well, only one met the performance of human screeners.
Although some artificial intelligence software tested reasonably well, only one met the performance of human screeners.
Organ-on-a-chip technology has the potential to revolutionize drug development. Researchers have succeeded in putting various types of tissue onto chips.
Researchers have developed a deep learning system that may help detecting diabetic eye diseases, which could make doctors’ work easier and reduce healthcare cost.
Pairing a smartphone to capture retinal images with an AI may offer a solution for better screening for diabetic retinopathy.
Researchers created a novel deep learning method that makes automated screenings for eye diseases such as diabetic retinopathy more efficient.
Researchers show how they can make an AI show how it's working, as well as let it diagnose more like a doctor, thus making AI-systems more relevant to clinical practice.
Researchers developed wirelessly driven ‘smart contact lens’ technology that can detect diabetes and further treat diabetic retinopathy just by wearing them.
Physicians have been using automatic digital retinal screening, without assistance from an ophthalmologist, to detect diabetic retinal disease.
Biomedical engineers have developed a portable optical coherence tomography scanner that promises to bring the vision-saving technology to underserved regions.
The advent of electronic medical records with large image databases, along with advances in AI with deep learning, is offering medical professionals new opportunities to improve image analysis and disease diagnostics.