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Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder

Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder

Tanu, Deepti Kakkar
Copyright: © 2019 |Volume: 10 |Issue: 3 |Pages: 17
ISSN: 1947-315X|EISSN: 1947-3168|EISBN13: 9781522566663|DOI: 10.4018/IJEHMC.2019070105
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MLA

Tanu, and Deepti Kakkar. "Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder." IJEHMC vol.10, no.3 2019: pp.79-95. http://doi.org/10.4018/IJEHMC.2019070105

APA

Tanu & Kakkar, D. (2019). Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder. International Journal of E-Health and Medical Communications (IJEHMC), 10(3), 79-95. http://doi.org/10.4018/IJEHMC.2019070105

Chicago

Tanu, and Deepti Kakkar. "Diagnostic Assessment Techniques and Non-Invasive Biomarkers for Autism Spectrum Disorder," International Journal of E-Health and Medical Communications (IJEHMC) 10, no.3: 79-95. http://doi.org/10.4018/IJEHMC.2019070105

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Abstract

Autism spectrum disorder (ASD) is a complex heterogeneous neurological disorder that has led to a spectrum of diagnosis techniques. The screening instruments, medical and technological tools initiate the diagnosis process. Clinicians and psychologists propose therapies depending on the examination done by these methodologies. The literature has accounted dozens of diagnostic methods and alternative and complementary therapies but still lack in highlighting the proper biomarker for early detection and intervention. The emerging multi-modal neuro-imaging techniques have correlated the brain's functional and structural measures and diagnosed ASD with more sensitivity than individual approaches. The purpose of this review article is: (i) to provide an overview of the emerging ASD diagnosis methods and different markers and; (ii) to present the idea of integrating all the individual methods in to a multi-modal diagnostic system to enhance detection sensitivity. This system possesses the potential to diagnose and predict ASD clinically, neurologically & objectively with high detection sensitivity.

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