Open AccessLearning from Everyday Images Enables Expert-like Diagnosis of Retinal Diseases
Author(s) -
Ladislav Rampášek,
Anna Goldenberg
Publication year - 2018
Publication title -
cell
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 26.304
H-Index - 776
eISSN - 1097-4172
pISSN - 0092-8674
DOI - 10.1016/j.cell.2018.02.013
Subject(s) - medical diagnosis , artificial intelligence , medical imaging , computer science , visualization , machine learning , magnetic resonance imaging , deep learning , medical physics , convolutional neural network , radiology , medicine
Kermany et al. report an application of a neural network trained on millions of everyday images to a database of thousands of retinal tomography images that they gathered and expert labeled, resulting in a rapid and accurate diagnosis of retinal diseases.
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