A Stochastic Gradient Descent Support Vector Classification (SGD-SVC) Empowered Framework for Precise, Early Autism Detection in Toddlers

The ability to accurately and early recognize the autism spectrum disorder (ASD) is a critical factor in enabling effective early intervention strategies. This study proposes a novel framework that conceptualizes a synergistic combination of Stochasti

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Published
2025-10-08
DOI
https://doi.org/10.22541/au.175994550.07107471/v1
Primary Topic
Autism Spectrum Disorder Research
Type
article
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article

A Stochastic Gradient Descent Support Vector Classification (SGD-SVC) Empowered Framework for Precise, Early Autism Detection in Toddlers

Parul Arora, M. N. Hoda, Ritika Wason, Akshay Sobti
Autism Spectrum Disorder Research
article

A Stochastic Gradient Descent Support Vector Classification (SGD-SVC) Empowered Framework for Precise, Early Autism Detection in Toddlers

Parul Arora, M. N. Hoda, Ritika Wason, Akshay Sobti
article en

Abstract

The ability to accurately and early recognize the autism spectrum disorder (ASD) is a critical factor in enabling effective early intervention strategies. This study proposes a novel framework that conceptualizes a synergistic combination of Stochasti

Applications Research (United States) (US)
Openalex Percentile: Top 72%
Autism Spectrum Disorder Research
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A Stochastic Gradient Descent Support Vector Classification (SGD-SVC) Empowered Framework for Precise, Early Autism Detection in Toddlers — Parul Arora, M. N. Hoda, et al. · (2025) | TGRS Research Map | TGRS