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Creating artificial intelligence solutions in E-health infrastructure to support disabled people. / Grigoryan, David; Muradov, Avetik; Balyan, Serob; Abrahamyan, Suren; Katvalyan, Armine; Korkhov, Vladimir; Iakushkin, Oleg; Kulabukhova, Natalia; Shchegoleva, Nadezhda.

In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 10963, 04.07.2018, p. 41-50.

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Grigoryan D, Muradov A, Balyan S, Abrahamyan S, Katvalyan A, Korkhov V et al. Creating artificial intelligence solutions in E-health infrastructure to support disabled people. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2018 Jul 4;10963:41-50. https://doi.org/10.1007/978-3-319-95171-3_4

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BibTeX

@article{f34ef09abf794f218885a1211c405038,
title = "Creating artificial intelligence solutions in E-health infrastructure to support disabled people",
abstract = "Recently, the creation of a barrier-free environment for disabled people is becoming more and more important. All this is done so that people do not feel difficulties in filing their ordinary needs, including communication. For this purpose, a communicator application was developed that allows communication using card-pictograms for people with speech and writing disorders, particularly people with ASD. According to the US National Center for Health Statistics and the Health Resources and Services Administration, in 2011–2012 Autism was detected in 2% of schoolchildren worldwide, and this problem is very relevant. This article discusses several approaches of using Artificial Intelligence to simplify text typing with pictogram based cards by predictive input, which allows users faster compose messages and simplify communication process. A tool for analyzing the texts semantics - Word2Vec, was used, which is a neural network of direct distribution. Two approaches are considered: Continuous Bag of Words and Skip-gram. Also quality measures of advisory systems were used, and an approach giving the best results was identified. Besides that, quality measurements were carried out to identify optimal solutions of sentiment analysis to automatically detect suspicious messages sent by the users with such disabilities, which will help doctors to enhance their capabilities of monitoring and behavioral control and take appropriate actions if undesirable behavior of patient is detected by the system.",
keywords = "Artificial intelligence, E-Health, Information retrieval, Learning technologies, Mobile computing",
author = "David Grigoryan and Avetik Muradov and Serob Balyan and Suren Abrahamyan and Armine Katvalyan and Vladimir Korkhov and Oleg Iakushkin and Natalia Kulabukhova and Nadezhda Shchegoleva",
year = "2018",
month = jul,
day = "4",
doi = "10.1007/978-3-319-95171-3_4",
language = "English",
volume = "10963",
pages = "41--50",
journal = "Lecture Notes in Computer Science",
issn = "0302-9743",
publisher = "Springer Nature",
note = "18th International Conference on Computational Science and Its Applications, ICCSA 2018 ; Conference date: 02-07-2018 Through 05-07-2018",

}

RIS

TY - JOUR

T1 - Creating artificial intelligence solutions in E-health infrastructure to support disabled people

AU - Grigoryan, David

AU - Muradov, Avetik

AU - Balyan, Serob

AU - Abrahamyan, Suren

AU - Katvalyan, Armine

AU - Korkhov, Vladimir

AU - Iakushkin, Oleg

AU - Kulabukhova, Natalia

AU - Shchegoleva, Nadezhda

PY - 2018/7/4

Y1 - 2018/7/4

N2 - Recently, the creation of a barrier-free environment for disabled people is becoming more and more important. All this is done so that people do not feel difficulties in filing their ordinary needs, including communication. For this purpose, a communicator application was developed that allows communication using card-pictograms for people with speech and writing disorders, particularly people with ASD. According to the US National Center for Health Statistics and the Health Resources and Services Administration, in 2011–2012 Autism was detected in 2% of schoolchildren worldwide, and this problem is very relevant. This article discusses several approaches of using Artificial Intelligence to simplify text typing with pictogram based cards by predictive input, which allows users faster compose messages and simplify communication process. A tool for analyzing the texts semantics - Word2Vec, was used, which is a neural network of direct distribution. Two approaches are considered: Continuous Bag of Words and Skip-gram. Also quality measures of advisory systems were used, and an approach giving the best results was identified. Besides that, quality measurements were carried out to identify optimal solutions of sentiment analysis to automatically detect suspicious messages sent by the users with such disabilities, which will help doctors to enhance their capabilities of monitoring and behavioral control and take appropriate actions if undesirable behavior of patient is detected by the system.

AB - Recently, the creation of a barrier-free environment for disabled people is becoming more and more important. All this is done so that people do not feel difficulties in filing their ordinary needs, including communication. For this purpose, a communicator application was developed that allows communication using card-pictograms for people with speech and writing disorders, particularly people with ASD. According to the US National Center for Health Statistics and the Health Resources and Services Administration, in 2011–2012 Autism was detected in 2% of schoolchildren worldwide, and this problem is very relevant. This article discusses several approaches of using Artificial Intelligence to simplify text typing with pictogram based cards by predictive input, which allows users faster compose messages and simplify communication process. A tool for analyzing the texts semantics - Word2Vec, was used, which is a neural network of direct distribution. Two approaches are considered: Continuous Bag of Words and Skip-gram. Also quality measures of advisory systems were used, and an approach giving the best results was identified. Besides that, quality measurements were carried out to identify optimal solutions of sentiment analysis to automatically detect suspicious messages sent by the users with such disabilities, which will help doctors to enhance their capabilities of monitoring and behavioral control and take appropriate actions if undesirable behavior of patient is detected by the system.

KW - Artificial intelligence

KW - E-Health

KW - Information retrieval

KW - Learning technologies

KW - Mobile computing

UR - http://www.scopus.com/inward/record.url?scp=85049967024&partnerID=8YFLogxK

UR - http://www.mendeley.com/research/creating-artificial-intelligence-solutions-ehealth-infrastructure-support-disabled-people

U2 - 10.1007/978-3-319-95171-3_4

DO - 10.1007/978-3-319-95171-3_4

M3 - Article

AN - SCOPUS:85049967024

VL - 10963

SP - 41

EP - 50

JO - Lecture Notes in Computer Science

JF - Lecture Notes in Computer Science

SN - 0302-9743

T2 - 18th International Conference on Computational Science and Its Applications, ICCSA 2018

Y2 - 2 July 2018 through 5 July 2018

ER -

ID: 35284038