使用机器学习技术预测儿童ASD

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摘要

自闭症谱系障碍(ASD)是一种神经系统疾病,从儿童早期开始,一直贯穿于个体的现实生活中。它会影响个人的行为、与他人的谈话、干扰和学习。不管怎样,现在自闭症谱系障碍要在开始阶段加以区分,这是可以想象的。对自闭症谱系障碍的早期认识将改善该特定儿童的总体心理健康。将机器学习方法应用于自闭症谱系障碍(ASD)的诊断,在这项工作中,我们在ASD数据集上使用了机器学习技术和优化。我们对考虑的数据集采用了XGBoost算法,因此获得了高效的输出。这将是令人难以置信的,因为医生可以帮助他们在早期阶段识别自闭症谱系障碍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Prediction of ASD among Children using Machine Learning Techniques
Autism spectrum disorder (ASD) is a neurological issue that begins from early in childhood and proceeds all through such an individual's reality. It will influence that individual's conduct, speech with others, interference, and learning. Right now anyway, Autism Spectrum Disorder is to be distinguished in the beginning period, which is conceivable. Early acknowledgment of Autism Spectrum Disorder will improve the general psychological wellness of that particular youngster. The machine learning methodology is applied to diagnose Autism Spectrum Disorder (ASD), and in this work, we have used machine learning techniques and Optimization on an ASD dataset. We have employed XGBoost algorithms to the dataset considered, and as a result, efficient outputs are obtained. This will be incredible for the use of doctors to help them recognize Autism Spectrum Disorder at an early prior stage.
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