Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning

Osborne John D.; Wyatt Matthew; Westfall Andrew O.; Willig James; Bethard Steven; Gordon Geoff

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Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning

机译：使用自然语言处理和机器学习有效识别国家授权的可报告癌症病例

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摘要

Objective To help cancer registrars efficiently and accurately identify reportable cancer cases.

机译：目的帮助癌症登记员有效，准确地识别可报告的癌症病例。

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来源
《Journal of the American Medical Informatics Association :》 |2016年第6期|共8页
作者
Osborne John D.; Wyatt Matthew; Westfall Andrew O.; Willig James; Bethard Steven; Gordon Geoff;
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正文语种 eng
中图分类情报学、情报工作;
关键词
natural language processing; machine learning; information extraction; neoplasms; electronic health records; user-computer interface;

机译：自然语言处理机器学习信息提取肿瘤电子病历用户计算机界面;

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1. Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning [J] . Osborne John D., Wyatt Matthew, Westfall Andrew O., Journal of the American Medical Informatics Association : . 2016,第6期

机译：使用自然语言处理和机器学习有效识别国家授权的可报告癌症病例
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4. UTA_DLNLP at SemEval-2016 Task 12: Deep Learning Based Natural Language Processing System for Clinical Information Identification from Clinical Notes and Pathology Reports [C] . Peng Li, Heng Huang International workshop on semantic evaluation;Conference of the North American Chapter of the Association for Computational Linguistics - Human Language Technologies . 2016

机译：UTA_DLNLP在SemEval-2016任务12：基于深度学习的自然语言处理系统，用于从临床笔记和病理报告中识别临床信息
5. Leveraging unstructured construction injury reports to predict safety outcomes and model safety risk using Natural Language Processing, Machine Learning, and probability theory [D] . Tixier, Antoine Jean-Pierre. 2015

机译：利用非结构化施工损伤报告以预测使用自然语言处理，机器学习和概率理论来预测安全结果和模型安全风险
6. Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning [O] . John D Osborne, Matthew Wyatt, Andrew O Westfall, 2016

机译：使用自然语言处理和机器学习有效识别国家授权的可报告癌症病例
7. Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning [O] . John D Osborne, Matthew Wyatt, Andrew O Westfall, 2016

机译：利用自然语言加工和机器学习有效地识别国家授权的可报告癌症病例

Efficient identification of nationally mandated reportable cancer cases using natural language processing and machine learning

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