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Optimized Artificial Intelligence for Enhanced Ectasia Detection Using Scheimpflug-Based Corneal Tomography and
Renato Ambrósio1, Aydano P Machado2, Edileuza Leão3
1From the Department of Ophthalmology, the Federal University of the State of Rio de Janeiro, Brazil; Rio de Janeiro Corneal Tomography and Biomechanics Study Group, Rio de Janeiro, Brazil; Department of Ophthalmology, Federal University of São Paulo, São Paulo, Brazil; Brazilian Artificial Intelligence Networking in Medicine (BrAIN), Maceio and Rio de Janeiro, Brazil; World College of Refractive Surgery & Visual Sciences, Scottsdale, Arizona, USA.
Optimized artificial intelligence (AI) algorithms integrating Scheimpflug-based corneal tomography and biomechanics improve ectasia detection accuracy. The novel TBIv2 algorithm shows enhanced performance in identifying subtle forms of ectasia.
Failed At:
2026-06-19T13:49:00.125868+00:00
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