Classification of Alzheimer’s disease using convolutional neural network based on brain MRI image

Memory disorders are often experienced by someone who has entered old age caused because nerve cells (neurons) in the part of the brain involved in cognitive function have been damaged and are no longer functioning properly. It is commonly called dementia or Alzheimer’s. Symptoms arising from Alzhei...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Wildah, Siti Khotimatul, Agustiani, Sarifah, Mustopa, Ali, Sulaiman, Hamdun, Rahmawati, Ami
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue 1
container_start_page
container_title
container_volume 2714
creator Wildah, Siti Khotimatul
Agustiani, Sarifah
Mustopa, Ali
Sulaiman, Hamdun
Rahmawati, Ami
description Memory disorders are often experienced by someone who has entered old age caused because nerve cells (neurons) in the part of the brain involved in cognitive function have been damaged and are no longer functioning properly. It is commonly called dementia or Alzheimer’s. Symptoms arising from Alzheimer’s disease such as memory impairment, personality changes, mood and behavior, and problems in daily interactions and activities due to confusion in digesting questions and messy memories. But until now there is no cure for the disease, therefore early detection is needed in order to prepare adequate treatment. The study aims to propose a method that can classify the development of Alzheimer’s disease by testing 6,400 brain MRI data. The method proposed in this study uses deep learning method with CNN algorithm and accuracy value obtained by 98.22%.
doi_str_mv 10.1063/5.0128556
format Conference Proceeding
fullrecord <record><control><sourceid>proquest_scita</sourceid><recordid>TN_cdi_scitation_primary_10_1063_5_0128556</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2811319904</sourcerecordid><originalsourceid>FETCH-LOGICAL-p168t-b93c36228436a88945287f08abb18244c0207c5a45bdbb9bdbf117922bfab8e43</originalsourceid><addsrcrecordid>eNp9kMtKAzEYhYMoWKsL3yDgTpia60yyLEVroSKIgruQzGRq6nQyJjMVXfkavp5P4vQC7tz8Z_Odw_kPAOcYjTBK6RUfIUwE5-kBGGDOcZKlOD0EA4QkSwijz8fgJMYlQkRmmRiAfFLpGF3pct06X0NfwnH1-WLdyoafr-8ICxetjhZ20dULmPt67atug-oK1rYLW2nffXiFpucK2IeYoF0N7x5m0K30wp6Co1JX0Z7tdQiebq4fJ7fJ_H46m4znSYNT0SZG0pymhAhGUy2EZJyIrERCG4MFYSxHBGU514ybwhjZnxLjTBJiSm2EZXQILna5TfBvnY2tWvou9EWjIgJjiqVEG-pyR8XctdunVRP6nuFDrX1QXO0HVE1R_gdjpDaL_xnoLy8ndAY</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype><pqid>2811319904</pqid></control><display><type>conference_proceeding</type><title>Classification of Alzheimer’s disease using convolutional neural network based on brain MRI image</title><source>American Institute of Physics (AIP) Journals</source><creator>Wildah, Siti Khotimatul ; Agustiani, Sarifah ; Mustopa, Ali ; Sulaiman, Hamdun ; Rahmawati, Ami</creator><contributor>Junaidi, Agus ; Agustiani, Sarifah ; Arifin, Yoseph Tajul ; Baidawi, Taufik ; Dalis, Sopiyan ; Haryani ; Hastuti, Dwi Puji</contributor><creatorcontrib>Wildah, Siti Khotimatul ; Agustiani, Sarifah ; Mustopa, Ali ; Sulaiman, Hamdun ; Rahmawati, Ami ; Junaidi, Agus ; Agustiani, Sarifah ; Arifin, Yoseph Tajul ; Baidawi, Taufik ; Dalis, Sopiyan ; Haryani ; Hastuti, Dwi Puji</creatorcontrib><description>Memory disorders are often experienced by someone who has entered old age caused because nerve cells (neurons) in the part of the brain involved in cognitive function have been damaged and are no longer functioning properly. It is commonly called dementia or Alzheimer’s. Symptoms arising from Alzheimer’s disease such as memory impairment, personality changes, mood and behavior, and problems in daily interactions and activities due to confusion in digesting questions and messy memories. But until now there is no cure for the disease, therefore early detection is needed in order to prepare adequate treatment. The study aims to propose a method that can classify the development of Alzheimer’s disease by testing 6,400 brain MRI data. The method proposed in this study uses deep learning method with CNN algorithm and accuracy value obtained by 98.22%.</description><identifier>ISSN: 0094-243X</identifier><identifier>EISSN: 1551-7616</identifier><identifier>DOI: 10.1063/5.0128556</identifier><identifier>CODEN: APCPCS</identifier><language>eng</language><publisher>Melville: American Institute of Physics</publisher><subject>Algorithms ; Artificial neural networks ; Brain damage ; Machine learning ; Magnetic resonance imaging ; Signs and symptoms</subject><ispartof>AIP Conference Proceedings, 2023, Vol.2714 (1)</ispartof><rights>Author(s)</rights><rights>2023 Author(s). Published by AIP Publishing.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://pubs.aip.org/acp/article-lookup/doi/10.1063/5.0128556$$EHTML$$P50$$Gscitation$$H</linktohtml><link.rule.ids>309,310,314,780,784,789,790,794,4512,23930,23931,25140,27924,27925,76384</link.rule.ids></links><search><contributor>Junaidi, Agus</contributor><contributor>Agustiani, Sarifah</contributor><contributor>Arifin, Yoseph Tajul</contributor><contributor>Baidawi, Taufik</contributor><contributor>Dalis, Sopiyan</contributor><contributor>Haryani</contributor><contributor>Hastuti, Dwi Puji</contributor><creatorcontrib>Wildah, Siti Khotimatul</creatorcontrib><creatorcontrib>Agustiani, Sarifah</creatorcontrib><creatorcontrib>Mustopa, Ali</creatorcontrib><creatorcontrib>Sulaiman, Hamdun</creatorcontrib><creatorcontrib>Rahmawati, Ami</creatorcontrib><title>Classification of Alzheimer’s disease using convolutional neural network based on brain MRI image</title><title>AIP Conference Proceedings</title><description>Memory disorders are often experienced by someone who has entered old age caused because nerve cells (neurons) in the part of the brain involved in cognitive function have been damaged and are no longer functioning properly. It is commonly called dementia or Alzheimer’s. Symptoms arising from Alzheimer’s disease such as memory impairment, personality changes, mood and behavior, and problems in daily interactions and activities due to confusion in digesting questions and messy memories. But until now there is no cure for the disease, therefore early detection is needed in order to prepare adequate treatment. The study aims to propose a method that can classify the development of Alzheimer’s disease by testing 6,400 brain MRI data. The method proposed in this study uses deep learning method with CNN algorithm and accuracy value obtained by 98.22%.</description><subject>Algorithms</subject><subject>Artificial neural networks</subject><subject>Brain damage</subject><subject>Machine learning</subject><subject>Magnetic resonance imaging</subject><subject>Signs and symptoms</subject><issn>0094-243X</issn><issn>1551-7616</issn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNp9kMtKAzEYhYMoWKsL3yDgTpia60yyLEVroSKIgruQzGRq6nQyJjMVXfkavp5P4vQC7tz8Z_Odw_kPAOcYjTBK6RUfIUwE5-kBGGDOcZKlOD0EA4QkSwijz8fgJMYlQkRmmRiAfFLpGF3pct06X0NfwnH1-WLdyoafr-8ICxetjhZ20dULmPt67atug-oK1rYLW2nffXiFpucK2IeYoF0N7x5m0K30wp6Co1JX0Z7tdQiebq4fJ7fJ_H46m4znSYNT0SZG0pymhAhGUy2EZJyIrERCG4MFYSxHBGU514ybwhjZnxLjTBJiSm2EZXQILna5TfBvnY2tWvou9EWjIgJjiqVEG-pyR8XctdunVRP6nuFDrX1QXO0HVE1R_gdjpDaL_xnoLy8ndAY</recordid><startdate>20230509</startdate><enddate>20230509</enddate><creator>Wildah, Siti Khotimatul</creator><creator>Agustiani, Sarifah</creator><creator>Mustopa, Ali</creator><creator>Sulaiman, Hamdun</creator><creator>Rahmawati, Ami</creator><general>American Institute of Physics</general><scope>8FD</scope><scope>H8D</scope><scope>L7M</scope></search><sort><creationdate>20230509</creationdate><title>Classification of Alzheimer’s disease using convolutional neural network based on brain MRI image</title><author>Wildah, Siti Khotimatul ; Agustiani, Sarifah ; Mustopa, Ali ; Sulaiman, Hamdun ; Rahmawati, Ami</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p168t-b93c36228436a88945287f08abb18244c0207c5a45bdbb9bdbf117922bfab8e43</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Artificial neural networks</topic><topic>Brain damage</topic><topic>Machine learning</topic><topic>Magnetic resonance imaging</topic><topic>Signs and symptoms</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wildah, Siti Khotimatul</creatorcontrib><creatorcontrib>Agustiani, Sarifah</creatorcontrib><creatorcontrib>Mustopa, Ali</creatorcontrib><creatorcontrib>Sulaiman, Hamdun</creatorcontrib><creatorcontrib>Rahmawati, Ami</creatorcontrib><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Advanced Technologies Database with Aerospace</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wildah, Siti Khotimatul</au><au>Agustiani, Sarifah</au><au>Mustopa, Ali</au><au>Sulaiman, Hamdun</au><au>Rahmawati, Ami</au><au>Junaidi, Agus</au><au>Agustiani, Sarifah</au><au>Arifin, Yoseph Tajul</au><au>Baidawi, Taufik</au><au>Dalis, Sopiyan</au><au>Haryani</au><au>Hastuti, Dwi Puji</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Classification of Alzheimer’s disease using convolutional neural network based on brain MRI image</atitle><btitle>AIP Conference Proceedings</btitle><date>2023-05-09</date><risdate>2023</risdate><volume>2714</volume><issue>1</issue><issn>0094-243X</issn><eissn>1551-7616</eissn><coden>APCPCS</coden><abstract>Memory disorders are often experienced by someone who has entered old age caused because nerve cells (neurons) in the part of the brain involved in cognitive function have been damaged and are no longer functioning properly. It is commonly called dementia or Alzheimer’s. Symptoms arising from Alzheimer’s disease such as memory impairment, personality changes, mood and behavior, and problems in daily interactions and activities due to confusion in digesting questions and messy memories. But until now there is no cure for the disease, therefore early detection is needed in order to prepare adequate treatment. The study aims to propose a method that can classify the development of Alzheimer’s disease by testing 6,400 brain MRI data. The method proposed in this study uses deep learning method with CNN algorithm and accuracy value obtained by 98.22%.</abstract><cop>Melville</cop><pub>American Institute of Physics</pub><doi>10.1063/5.0128556</doi><tpages>8</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0094-243X
ispartof AIP Conference Proceedings, 2023, Vol.2714 (1)
issn 0094-243X
1551-7616
language eng
recordid cdi_scitation_primary_10_1063_5_0128556
source American Institute of Physics (AIP) Journals
subjects Algorithms
Artificial neural networks
Brain damage
Machine learning
Magnetic resonance imaging
Signs and symptoms
title Classification of Alzheimer’s disease using convolutional neural network based on brain MRI image
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-28T11%3A59%3A11IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_scita&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Classification%20of%20Alzheimer%E2%80%99s%20disease%20using%20convolutional%20neural%20network%20based%20on%20brain%20MRI%20image&rft.btitle=AIP%20Conference%20Proceedings&rft.au=Wildah,%20Siti%20Khotimatul&rft.date=2023-05-09&rft.volume=2714&rft.issue=1&rft.issn=0094-243X&rft.eissn=1551-7616&rft.coden=APCPCS&rft_id=info:doi/10.1063/5.0128556&rft_dat=%3Cproquest_scita%3E2811319904%3C/proquest_scita%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2811319904&rft_id=info:pmid/&rfr_iscdi=true