Recommendation of refractive surgery through decision trees
DOI:
https://doi.org/10.15381/risi.v15i2.24780Keywords:
refractive surgery, decision tree, recommendation system, classification, ophthalmic informaticsAbstract
Introduction: This article presents the final results of the construction of a decision tree from a set of patient data for refractive surgery recommendation. Objective: To identify the favorable conditions for the recommendation of refractive surgery. Method: The PARTITION algorithm was used to build a decision tree from a set of patient data, which was then used to classify different examples. Results: An exhaustive review was carried out on the conditions to perform a refractive surgery. From a set of data and the established conditions, the decision tree was built. Conclusions: Decision trees serve as a classification and recommendation tool for undergoing refractive surgery.
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Copyright (c) 2022 Augusto Parcemon Cortez Vásquez, Miguel Angel Aguilar Luna Victoria
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