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Medical prescription classification: a NLP-based approach

机译:医疗处方分类:基于NLP的方法

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The digitization of healthcare data has been consolidated in the last decade as a must to manage the vast amount of data generated by healthcare organizations. Carrying out this process effectively represents an enabling resource that will improve healthcare services provision, as well as on-the-edge related applications, ranging from clinical text mining to predictive modelling, survival analysis, patient similarity, genetic data analysis and many others. The application presented in this work concerns the digitization of medical prescriptions, both to provide authorization for healthcare services or to grant reimbursement for medical expenses. The proposed system first extract text from scanned medical prescription, then Natural Language Processing and machine learning techniques provide effective classification exploiting embedded terms and categories about patient/doctor personal data, symptoms, pathology, diagnosis and suggested treatments. A REST ful Web Service is introduced, together with results of prescription classification over a set of 800K+ of diagnostic statements.
机译:在过去十年中,医疗数据的数字化已经得到了巩固,这是管理医疗组织生成的大量数据所必需的。有效地执行此过程表示一种可启用的资源,它将改善医疗保健服务的提供以及与边缘相关的应用程序,从临床文本挖掘到预测建模,生存分析,患者相似性,遗传数据分析等等。这项工作中提出的应用程序涉及医疗处方的数字化,既可以提供医疗保健服务的授权,也可以提供医疗费用的报销。提议的系统首先从扫描的医疗处方中提取文本,然后自然语言处理和机器学习技术利用嵌入的有关患者/医生个人数据,症状,病理,诊断和建议治疗的术语和类别来提供有效的分类。引入了REST ful Web服务,以及一组800K +诊断语句中的处方分类结果。

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