Autism Spectrum Disorder Prediction by Bio-inspired Algorithm with Blockchain based Database

A. S., W. Varuna
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Abstract

Autism Spectrum disorder can be diagnosed easily when it is identified earlier. In order to identify earlier, Machine learning algorithms and Bio-inspired algorithms are used. The characteristics of an individual is applied on Machine Learning to build the best accuracy models. In this proposed work the machine learning algorithm shows moderate accuracy level. In order to improve the accuracy level one of the Bio inspired algorithm are used. This proposed work shows the better accuracy level as 99.8% and the database are secured by using the Block chain Technology.
基于区块链数据库的仿生算法预测自闭症谱系障碍
如果早期发现自闭症谱系障碍,就很容易诊断出来。为了更早地识别,使用了机器学习算法和生物启发算法。将个体的特征应用于机器学习,以建立最佳的精度模型。在本工作中,机器学习算法显示出中等的精度水平。为了提高精度水平,采用了一种生物启发算法。该算法的准确率达到了99.8%,并且通过区块链技术对数据库进行了保护。
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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