Use of artificial intelligence to evaluate the detection of alterations in the retina as a screening test in Mexican patients

  • Dania Nimbe Lima-Sánchez Department of Biomedical Informatics, Medical school, UNAM
  • Moises Argueta-Santillan
  • E. Mahuina Campos-Castolo Departamento de Informática Biomédica Facultad de Medicina, Univ. Nacional Autónoma de México, México.
  • Miguel Angel Mendez-Lucero Departamento de Informática Biomédica, Facultad de Medicina, Univ. Nacional Autónoma de México, México.
  • Josué Fabricio Urbina-González Facultad de Ingeniería, Univ. Nacional Autónoma de México, México
  • Orlando Cerón-Solis Departamento de Informática Biomédica Facultad de Medicina, Univ. Nacional Autónoma de México, México.
  • Alejandro Alayola-Sansores Departamento de Informática Biomédica Facultad de Medicina, Univ. Nacional Autónoma de México, México.
  • German Fajardo-Dolci Director de la Facultad de Medicina, Univ. Nacional Autónoma de México, México
Keywords: Retinal image, Transfer learning, ocular disease classifier, ensemble methods, deep learning, convolutional networks

Abstract

In Mexico, chronic degenerative diseases are the main cause of morbidity, which have frequent complications in the retina, being the main cause of blindness in our population. Unfortunately, the detection of the pathology is usually late, which causes greater disability. To propose the detection of different pathologies, different artificial intelligence algorithms have been used for the images taken from the fundus. Objective. To evaluate different machine learning algorithms for screening of retinal alterations in the Mexican population. Methodology. We evaluate two types of models to estimate the screening capacity of artificial intelligence tools, one based on transfer learning, and ensemble methods against one based solely on convolutional networks. Results. We obtained adequate values to differentiate between healthy and sick, but not to diagnose different pathologies. Conclusion. It is necessary to expand the sample of images and improve the screening models

Published
2021-09-11
How to Cite
Lima-Sánchez, D. N., Argueta-Santillan, M., Campos-Castolo, E. M., Mendez-Lucero, M. A., Urbina-González, J. F., Cerón-Solis, O., Alayola-Sansores, A., & Fajardo-Dolci, G. (2021). Use of artificial intelligence to evaluate the detection of alterations in the retina as a screening test in Mexican patients. International Journal of Combinatorial Optimization Problems and Informatics, 12(3), 79-86. Retrieved from https://ijcopi.org/ojs/article/view/229
Section
Articles