Neural network guides keratoconus treatment, predicts outcomes with intracorneal rings

COPENHAGEN — A neural network based on a large database of keratoconus cases implanted with intracorneal ring segments can guide selection and intelligent surgical planning, predicting outcomes and optimizing results, according to a poster presented at the European Society of Cataract and Refractive Surgeons meeting.“Using the real-life data of 2,000 patients, we have selected the most representative, successful 400 cases. Through computer analysis of preoperative and postoperative data, a software selects, based on analogy, the cases that are most similar to the case you are going to treat as far as age, sex and all relevant corneal parameters. In this way we can plan our treatment and predict visual acuity, refraction and quality of vision,” Jorge Alió, MD, PhD, first author of the poster, said. “In simple words, the computer will tell you what to do in order to treat that patient successfully.”