International Journal of Multidisciplinary Research and Growth Evaluation  |  ISSN (Online): 2582-7138  |  Double-Blind Peer Review  |  Open Access  |  CC BY 4.0

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     2026:7/3

International Journal of Multidisciplinary Research and Growth Evaluation

ISSN (Online): 2582-7138 | Open Access

A Predictive Model for Early Diagnosis of Autism: Leveraging Machine Learning and Public Health Data

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Volume: 1 | Issue: 5 | Pages: 978-983

Subject: AutismDetection

Country: Nigeria

DOI: https://doi.org/10.54660/IJMRGE.2020.1.5.978-983

License: CC BY 4.0

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Abstract

Early diagnosis of autism is critical for improving developmental outcomes through timely intervention. Traditional diagnostic practices often face challenges, including resource constraints, delayed recognition of symptoms, and variability in diagnostic accuracy across populations. This paper explores the development of a predictive model leveraging machine learning and public health data to address these limitations. The integration of advanced algorithms with large-scale datasets enables identifying at-risk children at earlier stages of development. The proposed framework incorporates key components such as risk stratification, personalized intervention planning, and resource allocation optimization. Ethical considerations, including data privacy and algorithmic bias, are thoroughly examined to ensure equitable outcomes and ethical deployment. By synthesizing findings from existing predictive models, advancements in healthcare technologies, and public health applications, this paper underscores the transformative potential of predictive tools in autism care. It concludes with recommendations for implementation, emphasizing the need for collaborative efforts between healthcare providers, technology developers, and policymakers to realize the full benefits of this approach.

How to Cite This Article

Salewa Gloria Akinse, Ngozi Vivian Ekechi, Chiamaka Grace Ohanebo (2020). A Predictive Model for Early Diagnosis of Autism: Leveraging Machine Learning and Public Health Data . International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE), 1(5), 978-983. DOI: https://doi.org/10.54660/IJMRGE.2020.1.5.978-983

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Publication Information

Journal: International Journal of Multidisciplinary Research and Growth Evaluation (IJMRGE)

Publisher: Anfo Publication House

ISSN: 2582-7138 (Online)

Frequency: Bimonthly

Language: English

Open Access: Yes - This article is distributed under the terms of the Creative Commons Attribution 4.0 International License

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