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Stud Health Technol Inform ; 220: 124-9, 2016.
Article in English | MEDLINE | ID: mdl-27046564

ABSTRACT

Keratoconus is a progressive non-inflammatory disease of the cornea. Rigid gas permeable contact lenses (RGPs) are prescribed when the disease progresses. Contact lens fitting and assessment is very difficult in these patients and is a concern of ophthalmologists and optometrists. In this study, a hierarchical fuzzy system is used to capture the expertise of experienced ophthalmologists during the lens evaluation phase of prescription. The system is fine-tuned using genetic algorithms. Sensitivity, specificity and accuracy of the final system are 88.9%, 94.4% and 92.6% respectively.


Subject(s)
Algorithms , Contact Lenses , Decision Support Systems, Clinical/organization & administration , Keratoconus/rehabilitation , Prosthesis Fitting/methods , Therapy, Computer-Assisted/methods , Fuzzy Logic , Humans , Keratoconus/diagnosis , Machine Learning , Models, Genetic , Reproducibility of Results , Sensitivity and Specificity , Treatment Outcome
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