Prediction of Ayurvedic Herbs for Specific Diseases by Classification Techniques in Machine Learning

Priyanka Indoriya, S. Barde
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引用次数: 1

Abstract

India plays an important role in Ayurveda medicine and treatment because here is a storehouse of a lot of medicines. Ayurveda medicine is an ancient system that only rishi-Muni or Rajvidhya knew about it but now many people are interested to know about the Ayurveda medicinal plants. A traditional method for the prediction of suitable herbs where the Rajvedhya examines the pulse is known as Nadi Priksha now the scenario is changed many technologies is developed, and machines are able to perform such a task. The main purpose of this research is to design a system for all the people who prefer to use herbal medicine for diseases. In this paper, we predict the suitable herbs for the disease by the characteristics of Ayurveda herbs by using the classification technique of machine learning. For this, we collected data on 200 herbs and define the suitability of herbs for disease.
用机器学习中的分类技术预测阿育吠陀草药治疗特定疾病
印度在阿育吠陀医学和治疗中扮演着重要的角色,因为这里有很多药物的仓库。阿育吠陀医学是一个古老的系统,只有rishi-Muni或Rajvidhya知道它,但现在很多人都有兴趣了解阿育吠陀药用植物。一种传统的预测草药的方法被称为Nadi Priksha,现在情况发生了变化,许多技术被开发出来,机器能够执行这样的任务。本研究的主要目的是为所有喜欢使用草药治疗疾病的人设计一个系统。本文利用机器学习的分类技术,根据阿育吠陀草药的特点,预测适合该疾病的草药。为此,我们收集了200种草药的数据,并定义了草药对疾病的适用性。
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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