The R Journal: accepted article

This article will be copy edited and may be changed before publication.

Analysis of Corneal Data in R with the rPACI Package PDF download
Darío Ramos-López and Ana D. Maldonado

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/.

Received: 2020-10-30; online 2021-12-15, supplementary material, (1.1 Kb)
CRAN packages: rPACI, shiny, bnlearn
CRAN Task Views implied by cited CRAN packages: Bayesian, gR, HighPerformanceComputing, TeachingStatistics, WebTechnologies


CC BY 4.0
This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2021-099,
  author = {Darío Ramos-López and Ana D. Maldonado},
  title = {{Analysis of Corneal Data in R with the rPACI Package}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-099},
  url = {https://journal.r-project.org/archive/2021/RJ-2021-099/index.html}
}