AI Democratization in Optometry: Developing a Prototype with Azure Cognitive Services Platform

Authors

  • Shaun Baek Portola High School
  • Ryan Johnson Mentor, Portola High School
  • Claire Saunders Mentor, California Institute of Technology
  • Debora Lee Chen Mentor, School of Optometry, University of California Berkeley
  • Katherine Lai Mentor, School of Optometry, University of California Berkeley

DOI:

https://doi.org/10.47611/jsrhs.v10i3.1985

Keywords:

Telemedicine, Teleoptometry, Artificial Intelligence, AI Democratization

Abstract

As Artificial Intelligence (AI) technology advances, it is used in almost every aspect of our lives. However, AI is still complicated to implement without help from computer engineers. In the health care field, knowledge of medical and computer knowledge is necessary to create AI-based medical systems. Close cooperation between medical experts and computer experts is essential. For this reason, even if there has been a continuous effort to apply AI into the medical field, it has yet to be universalized. In particular, in the field of optometry and ophthalmology, more complex technology is required than in other medical fields because it is necessary to analyze an eye image to diagnose a disease. Therefore, this study explores the possibility for medical professionals with little computer knowledge in the field of ophthalmology to develop an AI-based diagnostic system without the help of computer engineers. In addition, it explores not only the possibilities but also the diagnostic accuracy of the developed system. Our results show that the diagnostic system discriminates against five common eye diseases to some extent. This study explores whether AI democratization is possible even in the field of ophthalmology that requires advanced skills and knowledge.

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References or Bibliography

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Published

11-05-2021

How to Cite

Baek, S., Johnson, R., Saunders, C., Lee Chen, D., & Lai, K. (2021). AI Democratization in Optometry: Developing a Prototype with Azure Cognitive Services Platform. Journal of Student Research, 10(3). https://doi.org/10.47611/jsrhs.v10i3.1985

Issue

Section

HS Research Articles