[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-125915-en":3,"doc-seo-125915-105":31,"detail-sidebar-cat-0-en-105":93},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":28,"seo_description":14,"update_tm":29,"read_time":30},125915,2336474466712,"Maeve","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",7,"Healthcare","LEVERAGING MACHINE LEARNING FOR EARLY AUTISM DETECTION VIA INDT-ASD INDIAN DATABASE - A PREPRINT","Machine learning supports earlier identification of neurodevelopmental conditions, with autism spectrum disorder (ASD) being a rapidly growing global concern. Clinical screening for autistic symptoms remains costly and time-consuming, motivating data-driven prediction from a clinically validated Indian ASD dataset. This preprint develops a fast, inexpensive ASD detection method using multiple ML classifiers and applies feature engineering on AIIMS Modified INDT-ASD (AMI) records collected in Delhi. Results show ASD can be predicted with a reduced set of 20 questions, achieving strong accuracy, with SVM performing best and a web solution added for Hindi and English use.","arXiv :2404 .02 18 1v 1 [ cs .LG] 2 Apr 2024  \nLEVERAGING MACHINE LEARNING FOR EARLY AUTISM DETECTION VIA INDT-ASD INDIAN DATABASE  \nA PREPRINT  \n Trapti Shrivastava∗  Harshal Chaudhari †  Vrijendra Singh ‡  \nABSTRACT  \nMachine learning (ML) has advanced quickly, particularly throughout the area of health care. The diagnosis of neurodevelopment problems using ML is a very important area of healthcare. Autism spectrum disorder (ASD) is one of the developmental disorders that is growing the fastest globally.  \nThe clinical screening tests used to identify autistic symptoms are expensive and time-consuming. But now that ML has been advanced, it’s feasible to identify autism early on. Previously, many different techniques have been used in investigations. Still, none of them have produced the anticipated outcomes when it comes to the capacity to predict autistic features utilizing a clinically validated Indian ASD database. Therefore, this study aimed to develop a simple, quick, and inexpensive technique for identifying ASD by using ML. Various machine learning classifiers, including Adaboost (AB), Gradient Boost (GB), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), Gaussian Naive Bayes (GNB), Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), K-Nearest Neighbors (KNN), and Support Vector Machine (SVM), were used to develop the autism prediction model. The proposed method was tested with records from the AIIMS Modified INDT-ASD (AMI) database, which were collected through an application developed by AIIMS in Delhi, India. Feature engineering has been applied to make the proposed solution easier than already available solutions. Using the proposed model, we succeeded in predicting ASD using a minimized set of 20 questions rather than the 28 questions presented in AMI with promising accuracy. In a comparative evaluation, SVM emerged as the superior model among others, with 100 ± 0.05% accuracy, higher recall by 5.34%, and improved accuracy by 2.22%-6.67% over RF. We have also introduced a web-based solution supporting both Hindi and English.  \nKeywords Autism · Machine learning · Prediction System · AIIMS Modified INCLEN Database · Healthcare  \n1 INTRODUCTION  \nMachine learning (ML) is all about bringing together various fields of study, especially as it leads to groundbreaking changes, particularly in the healthcare industry. ML can be used to create tools and processes that can easily and effectively do activities that would typically need human intellect Kusters et al. [2020] . A neuro-developmental disorder known as Autism Spectrum Disorder (ASD) is characterized by recurrent difficulties with speech and nonverbal communication, limited and repetitive behaviors, and social interaction Lord et al. [2020] . Numerous researchers have examined ASD in children aged eight years. According to research conducted in 2020, 23.1 to 44.9 out of every 1000 eight-year-old children in the US may have ASD Hughes et al. [2023] . Boys were more likely to be affected by autism than girls Maenner [2023] . Roughly 1 in 8 children in India may have a neurodevelopmental problem, and 1 in 100 children may have ASD Chakrabarti [2023] . Even with these noteworthy figures, no comprehensive research has been done for ASD on Indian data, the available data is scant.Patankar et al. [2022] . ASD is characterized by difficulties with communication and social skills, such as difficulty forming and maintaining friendships and interpreting body language. Individuals diagnosed with ASD may also exhibit repetitive habits and struggle with cognitive and learning  \n∗ shri .taps02@gmail .com Department of Information Technology, Indian Institute of Information Technology, Allahabad, 211013, India  \n†Department of Information Technology, Indian Institute of Information Technology, Allahabad, 211013, India ‡Department of Information Technology, Indian Institute of Information Technology, Allahabad, 211013, India  \nprocesses. In ","cbCaie48otIfBm1i","https://ap.wps.com/l/cbCaie48otIfBm1i","pdf",2068169,5,1,21,"English","en",105,"# Abstract\n# Introduction\n## Background on ASD and prevalence\n## Clinical screening tools and limitations","[{\"question\":\"Why is early autism detection important, and what challenge motivates this study?\",\"answer\":\"Early detection supports long-term child assistance, but clinical screening tests for autistic symptoms are expensive and time-consuming, prompting the need for quicker ML-based approaches.\"},{\"question\":\"How was the autism prediction model built in this work?\",\"answer\":\"The study used multiple machine learning classifiers (e.g., SVM, Random Forest, Logistic Regression, KNN) and applied feature engineering on AIIMS Modified INDT-ASD (AMI) records.\"},{\"question\":\"What model performed best and how many questions were required?\",\"answer\":\"SVM achieved the highest performance, with about 100% accuracy (reported as 100 ± 0.05%), and ASD prediction was achieved using a minimized set of 20 questions instead of the 28 used in AMI.\"}]","LEVERAGING MACHINE LEARNING FOR EARLY AUTISM DETECTION VIA INDT-ASD INDIAN DATABASE - A PREPRINT | PDF",1785902009,53,{"code":4,"msg":32,"data":33},"ok",{"site_id":25,"language":24,"slug":34,"title":13,"keywords":35,"description":14,"schema_data":36,"social_meta":88,"head_meta":90,"extra_data":92,"updated_unix":29},"leveraging-machine-learning-for-early-autism-detection-via-indt-asd-indian-database-a-preprint","",{"@graph":37,"@context":87},[38,55,70],{"@type":39,"itemListElement":40},"BreadcrumbList",[41,45,49,52],{"item":42,"name":43,"@type":44,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":46,"name":47,"@type":44,"position":48},"https://docshare.wps.com/document/","Document",2,{"item":50,"name":12,"@type":44,"position":51},"https://docshare.wps.com/document/healthcare/",3,{"item":53,"name":13,"@type":44,"position":54},"https://docshare.wps.com/document/leveraging-machine-learning-for-early-autism-detection-via-indt-asd-indian-database-a-preprint/125915/",4,{"url":53,"name":13,"@type":56,"author":57,"headline":13,"publisher":59,"fileFormat":62,"inLanguage":24,"description":14,"dateModified":63,"datePublished":64,"encodingFormat":62,"isAccessibleForFree":65,"interactionStatistic":66},"DigitalDocument",{"name":9,"@type":58},"Person",{"url":42,"name":60,"@type":61},"DocShare","Organization","application/pdf","2026-08-24","2026-08-05",true,{"@type":67,"interactionType":68,"userInteractionCount":20},"InteractionCounter",{"@type":69},"ViewAction",{"@type":71,"mainEntity":72},"FAQPage",[73,79,83],{"name":74,"@type":75,"acceptedAnswer":76},"Why is early autism detection important, and what challenge motivates this study?","Question",{"text":77,"@type":78},"Early detection supports long-term child assistance, but clinical screening tests for autistic symptoms are expensive and time-consuming, prompting the need for quicker ML-based approaches.","Answer",{"name":80,"@type":75,"acceptedAnswer":81},"How was the autism prediction model built in this work?",{"text":82,"@type":78},"The study used multiple machine learning classifiers (e.g., SVM, Random Forest, Logistic Regression, KNN) and applied feature engineering on AIIMS Modified INDT-ASD (AMI) records.",{"name":84,"@type":75,"acceptedAnswer":85},"What model performed best and how many questions were required?",{"text":86,"@type":78},"SVM achieved the highest performance, with about 100% accuracy (reported as 100 ± 0.05%), and ASD prediction was achieved using a minimized set of 20 questions instead of the 28 used in AMI.","https://schema.org",{"og:url":53,"og:type":89,"og:title":13,"og:site_name":60,"og:description":14},"article",{"robots":91,"canonical":53},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":94},[95,99,103,107,111,116,119,124,129,132,136],{"id":21,"doc_module":4,"doc_module_name":47,"category_name":96,"show_sort_weight":97,"slug":98},"Story & Novel",90,"story-novel",{"id":48,"doc_module":4,"doc_module_name":47,"category_name":100,"show_sort_weight":101,"slug":102},"Literature",80,"literature",{"id":54,"doc_module":4,"doc_module_name":47,"category_name":104,"show_sort_weight":105,"slug":106},"Exam",70,"exam",{"id":20,"doc_module":4,"doc_module_name":47,"category_name":108,"show_sort_weight":109,"slug":110},"Comic",60,"comic",{"id":112,"doc_module":4,"doc_module_name":47,"category_name":113,"show_sort_weight":114,"slug":115},6,"Technology",50,"technology",{"id":11,"doc_module":4,"doc_module_name":47,"category_name":12,"show_sort_weight":117,"slug":118},40,"healthcare",{"id":120,"doc_module":4,"doc_module_name":47,"category_name":121,"show_sort_weight":122,"slug":123},8,"Research & Report",30,"research-report",{"id":125,"doc_module":4,"doc_module_name":47,"category_name":126,"show_sort_weight":127,"slug":128},9,"Religion & Spirituality",20,"religion-spirituality",{"id":127,"doc_module":4,"doc_module_name":47,"category_name":130,"show_sort_weight":127,"slug":131},"World Cup","world-cup",{"id":133,"doc_module":4,"doc_module_name":47,"category_name":134,"show_sort_weight":133,"slug":135},10,"Lifestyle","lifestyle",{"id":137,"doc_module":4,"doc_module_name":47,"category_name":138,"show_sort_weight":20,"slug":139},19,"General","general"]