| 摘 要: 高血压是常见的慢性疾病，是心血管疾病的重要危险因素，但目前为止，尚未研制出根治高血压的特效 药物，具有一次得病，终身服药的特点。对于不同的人群，合理地选择降压药对于治疗高血压有重要意义。本文针对高 血压疾病治疗率低的问题，运用混合推理算法进行药物推荐，通过使用案例推理算法从案例库得到相似案例，进而用贝 叶斯推理算法得到相应的药物，并分别与案例推理和贝叶斯推理算法所得到的结果比较，实验表明，该混合推理算法在 一定程度上提高了药物推荐的准确率。 |
| 关键词: 高血压；案例推理；贝叶斯；混合推理；推荐 |
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中图分类号: TP18
文献标识码: A
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| Research on Hypertension Drug Recommendation Model Based on Hybrid Reasoning |
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CAO Xiaofeng
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( Department of Computer Engineering, Taiyuan Institute of Technology, Taiyuan 030008, China)
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| Abstract: Hypertension,as a common chronic disease,is a high risk factor of cardiovascular disease.However,no specific drug has been developed currently to cure hypertension.It has a characteristic of lifelong drug therapy once contracted. For different people,it is of great significance to choose the anti-hypertensive drugs reasonably for treatment.Aiming at the problem of low curing rate of hypertensive disease,hybrid reasoning algorithm has been used to drug recommendation. First of all,similar cases are collected by case-based reasoning algorithm,then the corresponding drugs are obtained by the Bayesian algorithm.The experiment,after comparing the results of the case-based reasoning with Bayesian,shows that to some extent,the hybrid reasoning algorithm improves the accuracy of drug recommendation. |
| Keywords: hypertension;case-based reasoning;Bayesian;hybrid reasoning;recommendation |
