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CommunicationOcular ExaminationOptical AppliancesOcular Disease

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This audio programme is in three parts, each discussing an area where technology can be used to improve optometric services to the public now and in the future.

  • AI and telemedicine in diabetic retinopathy screening: Dr Jorge Cuadros, an international expert on the use of AI in diabetic retinopathy, discusses the role of AI and telemedicine in the detection and grading of this sight threatening disease.  
  • Amyloid detection in screening for Alzheimer’s disease: Ms Anne Marie Cairns from Optos plc describes the latest research endeavours into early detection of Alzheimer's disease and discusses the potential role of ultra-widefield imaging in screening for the disease in the primary care environment.
  • The OrCam, the Oxsight and beyond: Dr Michael Crossland gives an informative update on recently available complex low vision aids and discusses the use of smart phone apps which have been designed to help the visually impaired carry out routine and specific tasks.

Last published: August 2020

    ◄Learning objectivesUnit 2 - Amyloid detection in screening for Alzheimer’s disease (~14 mins)►

    Unit 1 - AI and telemedicine in diabetic retinopathy screening (~21 mins)

    Unit 1 - AI and telemedicine in diabetic retinopathy screening (~21 mins)

    Dr Jorge Cuadros

    Diabetic retinopathy is emerging as a leading cause of preventable blindness globally. The use of artificial intelligence and machine learning is set to revolutionise the way clinicians gather and analyse clinical data. One of the recent trends has been the increasing use of portable systems to gather and transmit clinical data. In this interview we speak to Dr Jorge Cuadros, Santa Cruz based optometrist and co-founder of EyePACS, to find out more about the web-based application that allows for remote diagnosis of patients by off-site optometrists.

    • References

    • Bhaskaranand M, Ramachandra C, Bhat S, et al (2016) Automated Diabetic Retinopathy Screening and Monitoring Using Retinal Fundus Image Analysis. J Diabetes Sci Technol. 10(2) pp 254–261

      Bhaskaranand M, Ramachandra C, Bhat S, et al (2019) The Value of Automated Diabetic Retinopathy Screening with the EyeArt System: A Study of More Than 100,000 Consecutive Encounters from People with Diabetes. Diabetes Technol Ther. 21 (11) pp 635–643

      Gulshan V, Peng L, Coram M, et al (2016) Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs. JAMA. 316(22) pp 2402–2410

      Litvin T, Bresnick G, Cuadros J, et al (2017) A Revised Approach for the Detection of Sight-Threatening Diabetic Macular Edema. JAMA Ophthalmol. 135(1) pp 62–68

    ◄Learning objectivesUnit 2 - Amyloid detection in screening for Alzheimer’s disease (~14 mins)►