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基于机器学习技术的在线疾病识别、诊断和治疗。

Online Disease Identification and Diagnosis and Treatment Based on Machine Learning Technology.

机构信息

Jilin Medical University, Jilin 132013, China.

出版信息

J Healthc Eng. 2022 Apr 12;2022:6736249. doi: 10.1155/2022/6736249. eCollection 2022.

Abstract

The article uses machine learning algorithms to extract disease symptom keyword vectors. At the same time, we used deep learning technology to design a disease symptom classification model. We apply this model to an online disease consultation recommendation system. The system integrates machine learning algorithms and knowledge graph technology to help patients conduct online consultations. The system analyses the misclassification data of different departments through high-frequency word analysis. The study found that the accuracy rate of our machine learning algorithm model to identify entities in electronic medical records reached 96.29%. This type of model can effectively screen out the most important pathogenic features.

摘要

本文使用机器学习算法提取疾病症状关键词向量。同时,我们使用深度学习技术设计了疾病症状分类模型。我们将该模型应用于在线疾病咨询推荐系统。该系统集成了机器学习算法和知识图谱技术,帮助患者进行在线咨询。系统通过高频词分析对不同科室的分类错误数据进行研究,发现我们的机器学习算法模型识别电子病历中实体的准确率达到 96.29%。这种模型可以有效地筛选出最重要的致病特征。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca8b/9018189/a505f4922afb/JHE2022-6736249.001.jpg

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