AI in Healthcare June 26, 2019
Dave Pearson

Eyesight researchers have developed a machine-learning architecture whose best model, an ensemble classifier, achieved 93.4% accuracy in separating good candidates for corneal refractive surgery from patients likely to have post-surgery complications or poor outcomes.

The model performed much better than conventional screening methods and as well as highly experienced ophthalmologists who participated in the research.

The full study was published with open access in npj Digital Medicine.

Senior author Tyler Hyungtaek Rim of Singapore Eye Research Institute and colleagues trained five algorithms to identify appropriate surgery candidates.

From these overlapping tools...

Today's Sponsors

LEK
ZeOmega

Today's Sponsor

LEK

 
Topics: AI (Artificial Intelligence), Health System / Hospital, Patient / Consumer, Physician, Provider, Technology
Regulations, Innovations and AI Define This Week in Big Tech
Why health system AI predictions can fail
10 things you may have suspected about AI but didn’t know for sure till now
Meta's new AI assistant is rolling out across WhatsApp, Instagram, Facebook and Messenger
Exclusive: Powerful new AI model accurately converts speech to text, even your company's jargon

Share This Article