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首页> 外文期刊>Indian Journal of Science and Technology >Tumour Classification and Analysis from Breast Cancer Pathology Reports using Natural Language Processing
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Tumour Classification and Analysis from Breast Cancer Pathology Reports using Natural Language Processing

机译:使用自然语言处理从乳腺癌病理报告中进行肿瘤分类和分析

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摘要

Breast Cancer is the prime cause of death in Indian women. Hospitals in India use electronic means of collection and reporting of data. One such report is the Pathology report which has natural language narrations of the conditions of patients. This work aims to extract the details on Tumour (T) in the breast using pattern-matching rules and derive the pathological classification of T by applying the PTNM classification protocol by American Joint Committee on Cancer (AJCC). Information Retrieval (IR), Natural Language Processing (NLP) tasks and Information Extraction (IE) techniques are applied to develop an automated system to accomplish the task. The system analyzes the extracted and the classified values of T against the Gold Standard Values, which are derived by manual scrutiny of the reports. The evaluation of the performance of the automated system performed using three sets of Pathology reports, resulted in an average Precision of 86%, Recall of 82.7%, Specificity of 75.1% and Accuracy of 79.53%.
机译:乳腺癌是印度女性死亡的主要原因。印度的医院使用电子方式收集和报告数据。这样的报告之一就是《病理学》报告,其中包含了有关患者状况的自然语言叙述。这项工作旨在使用模式匹配规则来提取乳腺肿瘤(T)的细节,并通过应用美国癌症联合委员会(AJCC)的PTNM分类协议得出T的病理学分类。信息检索(IR),自然语言处理(NLP)任务和信息提取(IE)技术被用于开发完成任务的自动化系统。系统通过对报告的手动检查得出的金标准值来分析T的提取值和分类值。使用三套病理报告对自动化系统的性能进行评估,得出平均精度为86%,召回率为82.7%,特异性为75.1%,准确性为79.53%。

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