• Ms.CHAITHALI C SHETTY
• Dr. Shashidhar Kini K

We predict Autism Spectrum Disorder (ASD) using machine learning models by analysing behavioural, clinical, and genetic data. Algorithms such as Support Vector Machines (SVM), Random Forest, and Deep Neural Networks are evaluated using accuracy, precision, recall, and F1-score. The results demonstrate improved diagnostic accuracy, enabling early detection and personalized intervention strategies. This approach enhances ASD screening, supports clinical decision-making, and provides data- driven insights into key predictors of ASD. By leveraging AI, our framework offers a scalable and accessible tool for early diagnosis, improving outcomes in diverse clinical and non-clinical settings.

Autism Spectrum Disorder, Machine Learning, Early Diagnosis, Predictive Modeling, Behavioral Analysis, Clinical Data Mining, Personalized Intervention, Multi-modal Data, ASD Severity Prediction, Healthcare AI.

"AUTISM SPECTRUM DISORDER PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 7, page no.1150-1153, July-2025, Available :http://www.jetir.org/papers/JETIRGX06221.pdf

"AUTISM SPECTRUM DISORDER PREDICTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 7, page no. pp1150-1153, July-2025, Available at : http://www.jetir.org/papers/JETIRGX06221.pdf