Analysis of Autism Spectrum Disorder in Children with the Prepared Dataset: A Machine Learning Approach for Prediction

P. Ramya, G. Geetha, Vattikuti NagaPrudhvi Raj
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引用次数: 1

Abstract

Right now Autism Spectrum Disorder (ASD) is at fastest pace in these days quicker than any other times. Regardless of the way that number of studies have been taken using different procedures, no particular study have stated the purposes behind the Autism. It is the “spectrum” disorder which of the fact that is wide in the sort and seriousness of the side effects to the individuals who experience this. Autism might occur any ethnic, racial and monetary related social gatherings. Disregarding the fact that autism spectrum disorder might be a profound established issue, yet the physical and mental treatments, medications, organizations can improve a person’s manifestations and capacity. Our work primarily focuses around the expectation of the medically introverted kids who are underneath 4 years. SVM Support Vector Machine is utilized for the order of the dataset to anticipate the autism spectrum disorder in children and to say the specific stage the kid is in.
用预备数据集分析儿童自闭症谱系障碍:一种机器学习预测方法
目前,自闭症谱系障碍(ASD)的发展速度最快,比以往任何时候都快。不管有多少研究采用了不同的方法,没有一项研究阐明了自闭症背后的目的。这是一种“谱系”障碍,事实上,对经历过这种疾病的人来说,副作用的种类和严重程度都很广泛。自闭症可能发生在任何与民族、种族和金钱有关的社交聚会上。尽管自闭症谱系障碍可能是一个根深蒂固的问题,但身体和精神治疗,药物,组织可以改善一个人的表现和能力。我们的工作主要集中在医学上内向的4岁以下儿童的期望。利用支持向量机支持向量机对数据集进行排序,预测儿童自闭症谱系障碍,判断儿童所处的具体阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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