Detecting Alzheimer’s Disease by Exploiting Linguistic Information from Nepali Transcript

Thapa, S; Adhikari, S; Naseem, U; Singh, P; Bharathy, G; Prasad, M

Detecting Alzheimer’s Disease by Exploiting Linguistic Information from Nepali Transcript

Thapa, S Adhikari, S Naseem, U Singh, P Bharathy, G

Prasad, M

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Publisher:: Springer International Publishing
Publication Type:: Conference Proceeding
Citation:: Communications in Computer and Information Science, 2020, 1332, pp. 176-184
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Thapa, S
dc.contributor.author	Adhikari, S
dc.contributor.author	Naseem, U
dc.contributor.author	Singh, P
dc.contributor.author	Bharathy, G https://orcid.org/0000-0001-8384-9509
dc.contributor.author	Prasad, M https://orcid.org/0000-0001-9719-2253
dc.date.accessioned	2021-03-16T01:47:02Z
dc.date.available	2021-03-16T01:47:02Z
dc.date.issued	2020-01-01
dc.identifier.citation	Communications in Computer and Information Science, 2020, 1332, pp. 176-184
dc.identifier.isbn	9783030638191
dc.identifier.issn	1865-0929
dc.identifier.issn	1865-0937
dc.identifier.uri	http://hdl.handle.net/10453/147233
dc.description.abstract	© 2020, Springer Nature Switzerland AG. Alzheimer’s disease (AD) is the most common form of neurodegenerating disorder accounting for 60–80% of all dementia cases. The lack of effective clinical treatment options to completely cure or even slow the progression of disease makes it even more serious. Treatment options are available to treat the milder stage of the disease to provide symptomatic short-term relief and improve quality of life. Early diagnosis is key in the treatment and management of AD as advanced stages of disease cause severe cognitive decline and permanent brain damage. This has prompted researchers to explore innovative ways to detect AD early on. Changes in speech are one of the main signs of AD patients. As the brain deteriorates the language processing ability of the patients deteriorates too. Previous research has been done in the English language using Natural Language Processing (NLP) techniques for early detection of AD. However, research using local languages and low resourced language like Nepali still lag behind. NLP is an important tool in Artificial Intelligence to decipher the human language and perform various tasks. In this paper, various classifiers have been discussed for the early detection of Alzheimer’s in the Nepali language. The proposed study makes a convincing conclusion that the difficulty in processing information in AD patients reflects in their speech while describing a picture. The study incorporates the speech decline of AD patients to classify them as control subjects or AD patients using various classifiers and NLP techniques. Furthermore, in this experiment a new dataset consisting of transcripts of AD patients and Control normal (CN) subjects in the Nepali language. In addition, this paper sets a baseline for the early detection of AD using NLP in the Nepali language.
dc.language	en
dc.publisher	Springer International Publishing
dc.relation.ispartof	Communications in Computer and Information Science
dc.relation.isbasedon	10.1007/978-3-030-63820-7_20
dc.rights	info:eu-repo/semantics/closedAccess
dc.title	Detecting Alzheimer’s Disease by Exploiting Linguistic Information from Nepali Transcript
dc.type	Conference Proceeding
utslib.citation.volume	1332
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - AAII - Australian Artificial Intelligence Institute
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
dc.date.updated	2021-03-16T01:47:00Z
pubs.publication-status	Published
pubs.volume	1332

Abstract:

© 2020, Springer Nature Switzerland AG. Alzheimer’s disease (AD) is the most common form of neurodegenerating disorder accounting for 60–80% of all dementia cases. The lack of effective clinical treatment options to completely cure or even slow the progression of disease makes it even more serious. Treatment options are available to treat the milder stage of the disease to provide symptomatic short-term relief and improve quality of life. Early diagnosis is key in the treatment and management of AD as advanced stages of disease cause severe cognitive decline and permanent brain damage. This has prompted researchers to explore innovative ways to detect AD early on. Changes in speech are one of the main signs of AD patients. As the brain deteriorates the language processing ability of the patients deteriorates too. Previous research has been done in the English language using Natural Language Processing (NLP) techniques for early detection of AD. However, research using local languages and low resourced language like Nepali still lag behind. NLP is an important tool in Artificial Intelligence to decipher the human language and perform various tasks. In this paper, various classifiers have been discussed for the early detection of Alzheimer’s in the Nepali language. The proposed study makes a convincing conclusion that the difficulty in processing information in AD patients reflects in their speech while describing a picture. The study incorporates the speech decline of AD patients to classify them as control subjects or AD patients using various classifiers and NLP techniques. Furthermore, in this experiment a new dataset consisting of transcripts of AD patients and Control normal (CN) subjects in the Nepali language. In addition, this paper sets a baseline for the early detection of AD using NLP in the Nepali language.

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http://hdl.handle.net/10453/147233