Classification of Infarction using Random Forest

S. H. Rukmawan; F. R. Aszhari; Z. Rustam; J. Pandelaki

doi:10.1088/1742-6596/1752/1/012044

Classification of Infarction using Random Forest

S. H. Rukmawan, F. R. Aszhari, Z. Rustam, J. Pandelaki

Research output: Contribution to journal › Conference article › peer-review

4 Citations (Scopus)

Abstract

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.

Original language	English
Article number	012044
Journal	Journal of Physics: Conference Series
Volume	1752
Issue number	1
DOIs	https://doi.org/10.1088/1742-6596/1752/1/012044
Publication status	Published - 15 Feb 2021
Event	3rd International Conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019 - Makassar, Indonesia Duration: 9 Oct 2019 → 10 Oct 2019

Keywords

Classifiacation
infraction
random forest

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1088/1742-6596/1752/1/012044

Cite this

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title = "Classification of Infarction using Random Forest",

abstract = "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.",

keywords = "Classifiacation, infraction, random forest",

author = "Rukmawan, {S. H.} and Aszhari, {F. R.} and Z. Rustam and J. Pandelaki",

note = "Funding Information: This research supported financially by the Ministry of Research, Technology, and Higher Education Republic of Indonesia (KEMENRISTEKDIKTI) with PTUPT 2019 research grant scheme. The authors want to thanks Dr. dr. Jacub Pandelaki Sp. Rad(K) and the other people who help the author to finish this paper. Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 3rd International Conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019 ; Conference date: 09-10-2019 Through 10-10-2019",

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T1 - Classification of Infarction using Random Forest

AU - Rukmawan, S. H.

AU - Aszhari, F. R.

AU - Rustam, Z.

AU - Pandelaki, J.

N1 - Funding Information: This research supported financially by the Ministry of Research, Technology, and Higher Education Republic of Indonesia (KEMENRISTEKDIKTI) with PTUPT 2019 research grant scheme. The authors want to thanks Dr. dr. Jacub Pandelaki Sp. Rad(K) and the other people who help the author to finish this paper. Publisher Copyright: © Published under licence by IOP Publishing Ltd. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/2/15

Y1 - 2021/2/15

N2 - 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.

AB - 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.

KW - Classifiacation

KW - infraction

KW - random forest

UR - http://www.scopus.com/inward/record.url?scp=85101749490&partnerID=8YFLogxK

U2 - 10.1088/1742-6596/1752/1/012044

DO - 10.1088/1742-6596/1752/1/012044

M3 - Conference article

AN - SCOPUS:85101749490

SN - 1742-6588

VL - 1752

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

IS - 1

M1 - 012044

T2 - 3rd International Conference on Statistics, Mathematics, Teaching, and Research 2019, ICSMTR 2019

Y2 - 9 October 2019 through 10 October 2019

ER -

Classification of Infarction using Random Forest

Abstract

Keywords

UN SDGs

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