{"title":"Analysis of Corneal Data in R with the rPACI Package","authors":"D. Ramos-López, A. D. Maldonado","doi":"10.32614/rj-2021-099","DOIUrl":null,"url":null,"abstract":"In ophthalmology, the early detection of keratoconus is still a crucial problem. Placido disk corneal topographers are an essential tool in clinical practice, and many indices for diagnosing corneal irregularities exist. The main goal of this work is to present the R package rPACI , providing several functions to handle and analyze corneal data. This package implements primary indices of corneal irregularity (based on geometrical properties) and compound indices built from the primary ones, either using a generalized linear model, or as a Bayesian classifier using a hybrid Bayesian network and performing approximate inference. rPACI aims to make the analysis of corneal data accessible for practitioners and researchers in the field. Moreover, a shiny app was developed so that rPACI can be used in any web browser, in a truly user-friendly graphical interface, without installing R or writing any R code. It is openly deployed at https://admaldonado.shinyapps.io/rPACI/ .","PeriodicalId":20974,"journal":{"name":"R J.","volume":"30 1","pages":"253"},"PeriodicalIF":0.0000,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"R J.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32614/rj-2021-099","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In ophthalmology, the early detection of keratoconus is still a crucial problem. Placido disk corneal topographers are an essential tool in clinical practice, and many indices for diagnosing corneal irregularities exist. The main goal of this work is to present the R package rPACI , providing several functions to handle and analyze corneal data. This package implements primary indices of corneal irregularity (based on geometrical properties) and compound indices built from the primary ones, either using a generalized linear model, or as a Bayesian classifier using a hybrid Bayesian network and performing approximate inference. rPACI aims to make the analysis of corneal data accessible for practitioners and researchers in the field. Moreover, a shiny app was developed so that rPACI can be used in any web browser, in a truly user-friendly graphical interface, without installing R or writing any R code. It is openly deployed at https://admaldonado.shinyapps.io/rPACI/ .