International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Autism Prediction using Machine Learning |
|---|---|
| ABSTRACT | Autism Spectrum Disorder (ASD) presents significant challenges in early detection due to its diverse behavioral manifestations and reliance on subjective clinical evaluations. This paper introduces Autism Prediction Using Machine Learning, an integrated decision-support system designed to automate ASD screening using behavioral and demographic attributes. The system incorporates a complete machine learning pipeline, including data preprocessing, feature engineering, class-imbalance handling with SMOTE, and supervised learning models such as Decision Tree, Random Forest, and XGBoost. A dataset of 800 records was cleaned, encoded, and balanced to enhance predictive reliability. Experimental results demonstrate that the Random Forest classifier, optimized using RandomizedSearchCV, achieved the highest performance with a cross-validation accuracy of 93% and a final test accuracy of 81.88%. The proposed system offers a fast, scalable, and objective approach for ASD prediction, reducing dependence on specialist- driven assessments and enabling early-stage screening in both clinical and community environments. Delivered as a user-friendly interface and deployable model, the system effectively bridges the gap between advanced machine learning methodologies and real- world healthcare applications, supporting timely intervention and improved developmental outcomes. |
| AUTHOR | NAGASHRI J, MAMATHA V, SUKHI PATIL, VAISHAK S IYENGAR, VINAY V SIRSALMATT |
| VOLUME | 176 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1311099 |
| pdf/99_Autism Prediction using Machine Learning.pdf | |
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