Open AccessApplication of Artificial Neural Network Method as A Detection of Blood Fat Disorders in Images of Complete Blood Examination
Author(s) -
Catharitasa Bella Fortuna,
S.T. Franky Chandra Satria Arisgraha,
Puspa Erawati
Publication year - 2021
Publication title -
indonesian applied physics letters
Language(s) - English
Resource type - Journals
ISSN - 2745-3502
DOI - 10.20473/iapl.v2i2.31510
Subject(s) - backpropagation , blood lipids , artificial neural network , medicine , computer science , artificial intelligence , cholesterol
Based on various epidemiological studies, it is stated that blood lipids are the main risk factor for atherosclerosis that leads to coronary heart disease. In patients with blood lipid disorders, red blood cells undergo deformability so that their shape is flatter than normal red blood cells, which are round. The research entitled Application of Artificial Neural Network Method as Detection of Blood Fat Abnormalities in Image of Complete Blood Examination Results was conducted to help facilitate laboratory examinations. This research hopes that it will provide appropriate early detection to support the expert diagnosis. This research consists of two stages. The first stage is digital image processing to obtain area, perimeter, and eccentricity features. These three features will be used as input to the Backpropagation Neural Network program as the second stage. At this stage, blood lipid abnormalities are detected from features that have been obtained from image processing. The accuracy of detecting blood lipid abnormalities with ANN Backpropagation is 85%.