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Designing Automatic Coding Module of Cancer Open Text Pathology Reports Based on International Classification of Diseases for Oncology

机译：基于国际肿瘤分类的癌症开放文本病理报告自动编码模块设计

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Background: In the domain of clinical documents, all diseases are classified at templates by the world health organization and specific codes have been assigned to them. The goal of this study was automatic coding of cancer free texts based on International Classification of Diseases for Oncology (ICD-O-3) and evaluation of results. Methods: In this research, the preparation and development of one initial sample of automatic coding module on pathology reports open texts existing in PubMed’s cancer titles database is performed for exploitation of the information based on the texts related to cancer to coding the information based on ICD-O-3. After developing the algorithm for exploiting cancer phrases and the codes based on ICD-O-3 and converting them to code in programming environment, the required data for implementation and algorithm testing were performed and finally the obtained results were evaluated. Results: Automatic coding prepares the possibility of coding and listing information inside the text and also coding the existing titles of neoplasms at descriptive text of pathology reports and with an accuracy of approximately 70%. This study explained a simple stepwise approach to coding issues in medicine. Conclusions: It performed effectively on free texts and could be used as a decision support module in Health Information Systems to reduce coding errors.
机译：背景：在临床文件领域，世界卫生组织将所有疾病归类为模板，并为其指定了特定代码。这项研究的目标是根据国际肿瘤疾病分类学（ICD-O-3）对无癌文本进行自动编码和结果评估。方法：在这项研究中，准备并开发了一份自动的病理学编码模块初始样本，用于公开PubMed癌症标题数据库中存在的公开文本，以利用与癌症相关的文本为基础的信息来对基于ICD的信息进行编码-O-3。在开发了基于ICD-O-3的癌症词组和代码的挖掘算法并将其转换为程序设计环境中的代码后，进行了实现和算法测试所需的数据，最后对获得的结果进行了评估。结果：自动编码为在文本内编码和列出信息以及在病理报告的描述性文本上以约70％的准确度编码现有肿瘤名称提供了可能性。这项研究解释了一种简单的逐步编码医学问题的方法。结论：它对自由文本有效地执行，并且可以用作健康信息系统中的决策支持模块，以减少编码错误。

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