International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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AI-Powered Breakthroughs in Autism Spectrum Disorder (ASD) Identification

Author(s) Mr. Saichand Pasupuleti, Mr. Phanindra Sai Boyapati
Country India
Abstract Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition that affects millions globally, presenting a wide range of symptoms and challenges. Early and accurate identification is crucial for enabling timely intervention, which can significantly improve quality of life for those affected. Traditional diagnostic methods, primarily based on behavioral assessments, often face challenges such as late diagnosis and subjective variability in interpretation.
In this white paper, "AI-Powered Breakthroughs in Autism Spectrum Disorder Identification," we explore the transformative role of Artificial Intelligence (AI) in revolutionizing ASD diagnosis. AI technologies, including machine learning, neural networks, and deep learning, offer powerful tools for enhancing diagnostic accuracy and early detection. By leveraging diverse data sources, such as genetic information, neuroimaging, and behavioral data, AI systems can identify patterns and indicators of ASD that may be overlooked by conventional methods. The paper highlights a number of groundbreaking AI applications that have demonstrated significant improvements in the speed and precision of ASD diagnostics. These advancements not only promise earlier interventions but also enable more personalized treatment strategies, ultimately leading to better outcomes for individuals and their families.
However, alongside these promising opportunities, the paper also addresses the challenges inherent in integrating AI technologies into clinical practice. Ethical considerations, data privacy, and potential biases within AI algorithms warrant careful attention and underscore the need for interdisciplinary collaboration and robust oversight mechanisms. Looking ahead, the paper outlines future directions for AI in ASD identification, emphasizing the importance of continued research and innovation. By integrating AI with other technological advances, such as wearable health monitors and telehealth platforms, there is potential to further enhance diagnostic capabilities and accessibility. In conclusion, the application of AI in autism diagnosis represents a significant step forward in addressing the limitations of current practices. With commitment to responsible implementation and ongoing research, AI has the potential to transform ASD identification and improve the lives of those affected by this spectrum disorder.
Keywords ASD, neurodevelopmental condition, early identification, intervention, diagnostic methods, behavioral assessments, artificial intelligence, AI, machine learning, neural networks, deep learning, diagnostic accuracy, early detection, genetic information, neuroimaging, behavioral data, personalized treatment strategies, ethical considerations, data privacy, biases, interdisciplinary collaboration, wearable health monitors, telehealth platforms, diagnostics, subjective assessments, late diagnosis, symptom variability, cultural barriers, limited access, resource intensiveness, objective assessment, multimodal data, continuous learning, predictive analytics, cloud computing, big data, personalized interventions, healthcare costs, interpretability, integration, resource allocation, Development, Education, AI-Driven Technologies, Predictive Diagnostics, Targeted Therapies, Collaborative Platforms, Data Sharing, Algorithmic Bias, Transparency, Scalable Solutions, Healthcare, Diagnostic Processes, Monitoring, Caregivers, Clinicians, Public Trust
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 7, Issue 3, May-June 2025
Published On 2025-06-03
DOI https://doi.org/10.36948/ijfmr.2025.v07i03.46677
Short DOI https://doi.org/g9m278
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