基于随机森林分类器的疾病预测

Swatik Paul, Pinku Ranjan, Somesh Kumar, Arun Kumar
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引用次数: 4

摘要

本文设计了一种疾病预测系统,以个体输入的症状作为输入,向个体显示预测输出,即最可能的疾病。后端使用随机森林分类器算法进行预测。正在使用的数据集包括与41种疾病相关的132种症状。此外,该系统还可以根据用户的疾病建议预防措施和药物。这可以通过自动化流程将医生和患者投入的精力和时间降至最低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Disease Predictor Using Random Forest Classifier
In this paper, a disease prediction system has been designed that takes the symptoms entered by an individual as input and shows the predicted output i.e. the most probable disease to them. Random Forest Classifier algorithm is being used in the backend for prediction purposes. The dataset that is being used consists of 132 symptoms that are linked to 41 diseases. In addition, the system could also suggest precautions and medicines to the user based on their disease. This can minimize the efforts and time invested by the doctors and patients by automatizing the process.
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