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Applying Language Technologies on Healthcare Patient Records for Better Treatment of Bulgarian Diabetic Patients

机译:将语言技术应用于医疗记录以更好地治疗保加利亚糖尿病患者

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This paper presents a research project integrating language technologies and a business intelligence tool that help to discover new knowledge in a very large repository of patient records in Bulgarian language. The ultimate project objective is to accelerate the construction of the Register of diabetic patients in Bulgaria. All the information needed for the Register is available in the outpatient records, collected by the Bulgarian National Health Insurance Fund. We extract automatically from the records' free text essential entities related to the drug treatment such as drug names, dosages, modes of admission, frequency and treatment duration with precision 95.2%; we classify the records according to the hypothesis "having diabetes" with precision 91.5% and deliver these findings to decision makers in order to improve the public health policy and the management of Bulgarian healthcare system. The experiments are run on the records of about 436,000 diabetic patients.
机译:本文提出了一个集成了语言技术和商业智能工具的研究项目,该工具有助于在保加利亚语的大型患者病历库中发现新知识。最终的项目目标是加快保加利亚糖尿病患者登记簿的建设。保加利亚国民健康保险基金收集的门诊记录中提供了登记册所需的所有信息。我们从记录的自由文本中自动提取与药物治疗相关的基本实体,例如药物名称,剂量,入院方式,频率和治疗持续时间,精确度为95.2%;我们根据“患有糖尿病”的假设对记录进行分类,精确度为91.5%,并将这些发现提供给决策者,以改善公共卫生政策和保加利亚医疗体系的管理。实验是根据大约436,000名糖尿病患者的记录进行的。

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