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Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods.

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Title: Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods.
Authors: Rakshe, Chetan1, Kunneth, Suja2, Sundaram, Soumya3, Murugappan, Murugappan4,5,6, m.murugappan@kcst.edu.kw, Agastinose Ronickom, Jac Fredo1
Source: Neural Computing & Applications; Jul2024, Vol. 36 Issue 20, p12565-12585, 21p
Database: Applied Science & Technology Source
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Header DbId: aci
DbLabel: Applied Science & Technology Source
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PubType: Academic Journal
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  Data: Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods.
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  Data: <searchLink fieldCode="AU" term="%22Rakshe%2C+Chetan%22">Rakshe, Chetan</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AU" term="%22Kunneth%2C+Suja%22">Kunneth, Suja</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AU" term="%22Sundaram%2C+Soumya%22">Sundaram, Soumya</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AU" term="%22Murugappan%2C+Murugappan%22">Murugappan, Murugappan</searchLink><relatesTo>4,5,6</relatesTo>, <i>m.murugappan@kcst.edu.kw</i><br /><searchLink fieldCode="AU" term="%22Agastinose+Ronickom%2C+Jac+Fredo%22">Agastinose Ronickom, Jac Fredo</searchLink><relatesTo>1</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Neural+Computing+%26+Applications%22">Neural Computing & Applications</searchLink>; Jul2024, Vol. 36 Issue 20, p12565-12585, 21p
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=aci&AN=178316446
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        Value: 10.1007/s00521-024-09770-3
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      – Code: eng
        Text: English
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        StartPage: 12565
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      – TitleFull: Autism spectrum disorder diagnosis using fractal and non-fractal-based functional connectivity analysis and machine learning methods.
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            NameFull: Kunneth, Suja
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              Text: Jul2024
              Type: published
              Y: 2024
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              Value: 36
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