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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Autism Spectrum Disorder Detection in children using Deep Learning |
| Authors Name: | Devarasetty Hiranmai , Chitrao Srilakshmi Raghavendra , Gogikari Nikhitha , Mantha Shailaja |
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IJNRD_199768
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| Published Paper Id: | IJNRD2306385 |
| Published In: | Volume 8 Issue 6, June-2023 |
| DOI: | |
| Abstract: | Autism Spectrum Disorder is a neurodevelopmental condition. It is characterized by differences seen in social, cognitive and developmental skills. In autism spectrum disorder or autism, “Spectrum” refers to a variety of characteristics, behaviors and skills exhibited by a person with autism. One of the major causes of autism is genetics but early detection and treatment can improve the condition. Early symptoms of ASD start showing at the age of 3 years and above. Our paper mainly focuses on studying and detecting ASD in children from age 4-11 years using Deep Learning which can help automate the whole ASD diagnosis process. We have used a dataset consisting of 20 features with the screening test records of 292 patients. The main technology used here is Deep Neural Networks which can help detect if a child has ASD or not. The obtained results are predicted using binary numbers (0’s or 1’s). Among different classifiers in DL we used one such classifier which works best with binary classification and is called Logistic Regression (LR). Therefore, with the help of many DL approaches we built a system which is able to detect ASD in children with 95% accuracy and can become an alternative for standardized clinical tests and provide results in a short time. |
| Keywords: | Autism Spectrum Disorder, Deep Learning, Deep neural networks, Logistic Regression, clinical standard methods. |
| Cite Article: | "Autism Spectrum Disorder Detection in children using Deep Learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.8, Issue 6, page no.d815-d819, June-2023, Available :http://www.ijnrd.org/papers/IJNRD2306385.pdf |
| Downloads: | 000118752 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2306385 Registration ID: 199768 Published In: Volume 8 Issue 6, June-2023 DOI (Digital Object Identifier): Page No: d815-d819 Country: Hyderabad, Telangana, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2306385 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2306385 |
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ISSN: 2456-4184
Impact Factor: 8.76 and ISSN APPROVED
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