Open AccessClassification of Infarction using Random Forest
Author(s) -
S. H. Rukmawan,
F. R. Aszhari,
Zuherman Rustam,
Jacub Pandelaki
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1752/1/012044
Subject(s) - infarction , brain infarction , random forest , life expectancy , stroke (engine) , cerebral infarction , medicine , expectancy theory , emergency medicine , medical emergency , artificial intelligence , computer science , myocardial infarction , psychology , ischemia , environmental health , engineering , mechanical engineering , social psychology , population
Stroke is a condition caused by disruption in the blood supply to the brain. When the flow of blood is decreasing and resulting dead brain tissue that is called an infarction. If this condition not treated immediately and don’t get the right treatment will cause the death of the brain. Therefore, the classification of infarction is important to help increase the life expectancy of the patients. In this study, we are using infarction data from the Department of Radiology at Dr. Cipto Mangunkusumo Hospital and propose a random forest method to help the health sector for detecting infarction quickly and accurately. The best result by using the random forest method is 94.44 percent with 65 percent as training data.