Explainable AI Models for Adult Autism Detection and Interpretation

S. Amudha, Yashwanth Addakula, Vamsi Ravi

2025

Abstract

This research proposes the use of Explainable Artificial Intelligence (XAI) for detecting autism in adults despite the difficulties faced in making a diagnosis of autism spectrum disorders (ASD) in this group of individuals. Using a model that allows understanding the reasons for machine learning output, the study utilizes a range of behavioral, cognitive, and even physiological markers to detect the feature of autism while making sure the predictions made through the use of XAI, for example them being SHAP or LIME, are straightforward and self-explanatory. Such a provision improves understanding of the results and the reasons for making the diagnosis; which in turn fosters trust and facilitates interventions at the appropriate level and time among the caregivers. An incorporation of cutting-edge technologies and XAI provides diagnosis with precision and ease hence the process is not only multilevel but also clear. In conclusion, this model enhances autism assessment and interventions for adults with ASD, laying the groundwork essential for the compassionate and intelligent application of AI to medicine for the benefit of both healthcare professionals, and those diagnosed with ASD.

Paper Citation

in Harvard Style

Amudha S., Addakula Y. and Ravi V. (2025). Explainable AI Models for Adult Autism Detection and Interpretation. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 243-258. DOI: 10.5220/0013925900004919

in Bibtex Style

@conference{icrdicct`2525,
author={S. Amudha and Yashwanth Addakula and Vamsi Ravi},
title={Explainable AI Models for Adult Autism Detection and Interpretation},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={243-258},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013925900004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Explainable AI Models for Adult Autism Detection and Interpretation
SN - 978-989-758-777-1
AU - Amudha S.
AU - Addakula Y.
AU - Ravi V.
PY - 2025
SP - 243
EP - 258
DO - 10.5220/0013925900004919
PB - SciTePress