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  • AboutUs_Normal-24 The EyeCRO Approach
    • About Us
    • Careers
    • Location
    • Partners
  • MiDrops MiDROPS™
  • InVivo Models
    • Allergic Conjunctivitis
    • Corneal Sensitivity
    • Corneal Wound Healing
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    • DL-AAA Retinal Leakage
    • Dry Eye Disease
    • Endotoxin induced Uveitis
    • Experimental Autoimmune Uveitis
    • Geographic Atrophy
    • Inherited Retinal Degenerations
    • Ischemia Reperfusion Injury
    • Laser-induced Choroidal Neovascularization
    • Light Damaged
    • Mitochondrial Neuropathy
    • Optic Nerve Crush
    • Oxygen Induced Retinopathy
    • Retinal Detachment
    • Retinal Vein Occlusion
    • STZ-induced Diabetic Retinopathy
    • VEGF-induced permeability
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Preclinical Ophthalmic Contract Research

Detecting diabetic eye disease with machine learning

November 30, 2016 //  by stanselb

Diabetic retinopathy — an eye condition that affects people with diabetes — is the fastest growing cause of blindness, with nearly 415 million diabetic patients at risk worldwide. The disease can be treated if detected early, but if not, it can lead to irreversible blindness.  A few years ago, a Google research team began studying whether machine learning could be used to screen for diabetic retinopathy (DR). Today, in the Journal of the American Medical Association, we’ve published our results: a deep learning algorithm capable of interpreting signs of DR in retinal photographs, potentially helping doctors screen more patients, especially in underserved communities with limited resources.

Read the entire article here.

Category: NewsTag: blindness, diabetes, Diabetic retinopathy, ophthalmic, Ophthalmology, research

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