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Developed AI/ML algorithm to detect ‘cotton wool’ infection Spots in retina images for a Leading Healthcare Technology Provider in the US

Industry

Healthcare

Services

Digital Experience

 

Overview

The client is one of the leading healthcare technology providers in the US, offering technology that empowers care delivery solutions for ophthalmic hospitals.

 

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Challenges

 

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Detecting infection in the retina images, ‘cotton wool’ spots

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Transforming and automating the entire manual diagnosis process

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Calculating the spread of the infection and identifying the severity of the problem

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Improve the accuracy of diagnosis

 

 

 

 

Outcomes

 

  • The deep-learning algorithm can be extended to simultaneously identify multiple retinal abnormalities, helping practitioners improve the early diagnosis of retinal diseases in underdeveloped areas, thus addressing the triple mandates of care, viz., - accessibility, affordability, and availability 
  • This automated detection system can reduce manual effort, and primary eye care services can be provided in remote areas to overcome the scarcity of doctors
  • Accomplished a 95 percent decrease in exam time versus ophthalmologists working alone. The model helped lower exam time by 75 percent when combined with an ophthalmologist
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