Design of Convolutional Neural Network Modeling for Low-Density Lipoprotein (LDL) Levels Measurement Based on Iridology

Sayyidah Hanifah Putri, Adhi Harmoko Saputro

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Cholesterol is a waxy substance that contains fat required to produce hormones and other substances in the body. The excessive cholesterol in the blood vessel can be mixed with other substances and called Low-Density Lipoprotein (LDL). LDL can clog the blood vessel and caused heart disease and stroke. Measuring LDL levels is generally done by taking blood samples (invasive) with the lipid profile test method. This research focused on developing a non-invasive detection system for LDL levels status prediction based on eye image using Convolutional Neural Network (CNN) as a classification model. One indicator of excess LDL levels is a greyish-white ring that surrounds the iris called the corneal arcus. The image processing used the Circular Hough Transform (CHT) algorithm for the localization process and Rubber-Sheet Normalization to normalize the iris region. This LDL level status prediction system used CNN as a classification model with 5-fold cross-validation results in an accuracy of 97.14%.

Original languageEnglish
Title of host publicationICICoS 2020 - Proceeding
Subtitle of host publication4th International Conference on Informatics and Computational Sciences
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728195261
DOIs
Publication statusPublished - 10 Nov 2020
Event4th International Conference on Informatics and Computational Sciences, ICICoS 2020 - Semarang, Indonesia
Duration: 10 Nov 202011 Nov 2020

Publication series

NameICICoS 2020 - Proceeding: 4th International Conference on Informatics and Computational Sciences

Conference

Conference4th International Conference on Informatics and Computational Sciences, ICICoS 2020
CountryIndonesia
CitySemarang
Period10/11/2011/11/20

Keywords

  • Cholesterol
  • Convolutional neural network
  • Corneal arcus
  • Iridology
  • Low-Density Lipoprotein

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