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 | Predictive Analysis of Autism Spectrum Disorder Using Machine Learning an Intelligent Machine Learning-Based Web Framework for Early ASD Prediction |
|---|---|
| ABSTRACT | The project called “Predictive Analysis of Autism Spectrum Disorder Using Machine Learning” attempts to create a simple but efficient system that will be used to determine the likelihood of someone having the Autism Spectrum Disorder (ASD). The system involves filling out the basic information about the user, such as the age and gender and AQ-10 screening answers. The data provided by the user is analyzed through the use of a trained machine learning model, which predicts whether there is a likelihood of ASD among users. Various algorithms such as Logistic Regression, Decision Tree, Random Forest and Support Vector Machine were tried and the most accurate model was picked for the purpose. The algorithm is integrated into a Flask back end to provide better performance and results. Once the information is uploaded into the system, the user gets a result immediately together with the probability percentage and the AQ score. In doing so, the output becomes easy to interpret and useful for users. It should not be considered as an alternative to professional diagnostics; however, it can become a helpful preliminary tool for this purpose. As for the future perspectives for improvement of the proposed solution, one may suggest its development considering several aspects: patient’s medical history, enhanced modeling techniques, effective databases, and mobile applications. |
| AUTHOR | DR. T.V.S SRIRAM, K. RAMKRISHNA, P. PUJITHA Sr. Asst. Professor, Dept. of MCA, Nadimpalli Satyanarayana Raju Institute of Technology, Visakhapatnam, AP, India Asst. Professor, Dept. of MCA, Nadimpalli Satyanarayana Raju Institute of Technology, Visakhapatnam, AP, India Dept. of MCA, Nadimpalli Satyanarayana Raju Institute of Technology, Visakhapatnam, AP, India |
| VOLUME | 185 |
| DOI | DOI: 10.15680/IJIRCCE.2026.14060113 |
| pdf/113_Predictive Analysis of Autism Spectrum Disorder Using Machine Learning an Intelligent Machine Learning-Based Web Framework for Early ASD Prediction.pdf | |
| KEYWORDS | |
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