Learning entry profiles of children with autism from multivariate treatment information using restricted boltzmann machines

Pratibha Vellanki, Dinh Phung, Thi Duong, Svetha Venkatesh

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearch

1 Citation (Scopus)

Abstract

Entry profiles can be generated before children with Autism Spectrum Disorders (ASD) begin to traverse an intervention program. They can help evaluate the progress of each child on the dedicated syllabus in addition to enabling narrowing down the best intervention course over time. However, the traits of ASD are expressed in different ways in every individual affected. The resulting spectrum nature of the disorder makes it challenging to discover profiles of children with ASD. Using data from 491 children, traversing the syllabus of a comprehensive intervention program on iPad called TOBY Playpad, we learn the entry profiles of the children based on their age, sex and performance on their first skills of the syllabus. Mixed-variate restricted Boltzmann machines allow us to integrate the heterogeneous data into one model making it a suitable technique. The data based discovery of entry profiles may assist in developing systems that can automatically suggest best suitable paths through the syllabus by clustering the children based on the characteristics they present at the beginning of the program. This may open the pathway for personalised intervention.

Original languageEnglish
Title of host publicationTrends and Applications in Knowledge Discovery and Data Mining
Subtitle of host publicationPAKDD 2015 Workshops: BigPMA, VLSP, QIMIE, DAEBH Ho Chi Minh City, Vietnam, May 19–21, 2015 Revised Selected Papers
EditorsXiao-Li Li, Tru Cao, Ee-Peng Lim, Zhi-Hua Zhou, Tu-Bao Ho, David Cheung, Hiroshi Motoda
Place of PublicationCham Switzerland
PublisherSpringer
Pages245-257
Number of pages13
ISBN (Electronic)9783319256603
ISBN (Print)9783319256597
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventInternational Workshop on Data Analytics for Evidence-Based Healthcare 2015 - Ho Chi Minh City, Vietnam
Duration: 19 May 201522 May 2015
http://aihi.mq.edu.au/DAEBH2015/Home.html

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume9441
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Workshop on Data Analytics for Evidence-Based Healthcare 2015
Abbreviated titleDAEBH 2015
CountryVietnam
CityHo Chi Minh City
Period19/05/1522/05/15
Internet address

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