| 基于异构图嵌入学习的相似病案推荐 |
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| 引用本文： | 王亦凡,李继云. 基于异构图嵌入学习的相似病案推荐[J]. 计算机系统应用, 2020, 29(10): 228-234 |
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| 作者姓名： | 王亦凡 李继云 |
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| 作者单位： | 东华大学计算机科学与技术学院,上海201620;东华大学计算机科学与技术学院,上海201620 |
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| 基金项目： | 国家重点研发计划（2019YFE0190500）；上海市科学技术发展基金（18511102703） |
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| 摘 要： | 患者病案是医生在临床诊疗中的重要依据,准确的相似病案推荐可以很好地辅助医生进行临床决策.本文提出一种新的面向真实诊疗场景的患者病案表示模型,通过异构图嵌入对诊疗过程产生的患者病案中的医疗实体及其关系进行建模,服务于更好的病案推荐.基于某三甲医院乳腺诊疗病案数据表明该模型相较于现有的表示方法推荐准确率提升2%.
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| 关 键 词： | 表示学习 图嵌入 相似病案推荐 辅助诊疗 临床文本 |
| 收稿时间： | 2020-03-10 |
| 修稿时间： | 2020-04-10 |
Similar Medical Records Recommendation Based on Heterogeneous Graph Embedding Learning |
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| WANG Yi-Fan,LI Ji-Yun. Similar Medical Records Recommendation Based on Heterogeneous Graph Embedding Learning[J]. Computer Systems& Applications, 2020, 29(10): 228-234 |
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| Authors: | WANG Yi-Fan LI Ji-Yun |
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| Affiliation: | School of Computer Science and Technology, Donghua University, Shanghai 201620, China |
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| Abstract: | Medical records of patients are basic to the clinical diagnoses and treatments. Accurate recommendation of similar medical records can assist doctors in clinical decision making. In this study, we propose a new embedding model of medical records in real diagnosis and treatment scenarios. To recommend better medical records, we model the medical entities and their relationships in the medical records by heterogeneous graph embeddings. We conduct experiments on medical records of patients diagnosed with breast diseases from a Grade III-A hospital. The accuracy of the proposed model is improved by 2% compared with the existing model. |
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| Keywords: | representation learning graph embedding recommendation of similar medical records auxiliary diagnosis and treatment clinical text |
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