ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application
Abstract Background The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians’ healthcare practice, patients’ health management and public health literacy. High-quality corpus co...
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BMC
2020-07-01
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Series: | BMC Medical Informatics and Decision Making |
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Online Access: | http://link.springer.com/article/10.1186/s12911-020-1116-1 |
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doaj-7b91fe0567994edd9b72f4553bcb45cb |
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Article |
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DOAJ |
language |
English |
format |
Article |
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DOAJ |
author |
Hetong Ma Feihong Yang Jiansong Ren Ni Li Min Dai Xuwen Wang An Fang Jiao Li Qing Qian Jie He |
spellingShingle |
Hetong Ma Feihong Yang Jiansong Ren Ni Li Min Dai Xuwen Wang An Fang Jiao Li Qing Qian Jie He ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application BMC Medical Informatics and Decision Making Medical parallel corpus Cancer information Cross language Bilingual Cancer data HealthNLP |
author_facet |
Hetong Ma Feihong Yang Jiansong Ren Ni Li Min Dai Xuwen Wang An Fang Jiao Li Qing Qian Jie He |
author_sort |
Hetong Ma |
title |
ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application |
title_short |
ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application |
title_full |
ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application |
title_fullStr |
ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application |
title_full_unstemmed |
ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application |
title_sort |
eccparacorp: a cross-lingual parallel corpus towards cancer education, dissemination and application |
publisher |
BMC |
series |
BMC Medical Informatics and Decision Making |
issn |
1472-6947 |
publishDate |
2020-07-01 |
description |
Abstract Background The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians’ healthcare practice, patients’ health management and public health literacy. High-quality corpus containing cancer information is the necessary foundation of cancer education. Massive non-structural information resources exist in clinical narratives, electronic health records (EHR) etc. They can only be used for training AI models after being transformed into structured corpus. However, the scarcity of multilingual cancer corpus limits the intelligent processing, such as machine translation in medical scenarios. Thus, we created the cancer specific cross-lingual corpus and open it to the public for academic use. Methods Aiming to build an English-Chinese cancer parallel corpus, we developed a workflow of seven steps including data retrieval, data parsing, data processing, corpus implementation, assessment verification, corpus release, and application. We applied the workflow to a cross-lingual, comprehensive and authoritative cancer information resource, PDQ (Physician Data Query). We constructed, validated and released the parallel corpus named as ECCParaCorp, made it openly accessible online. Results The proposed English-Chinese Cancer Parallel Corpus (ECCParaCorp) consists of 6685 aligned text pairs in Xml, Excel, Csv format, containing 5190 sentence pairs, 1083 phrase pairs and 412 word pairs, which involved information of 6 cancers including breast cancer, liver cancer, lung cancer, esophageal cancer, colorectal cancer, and stomach cancer, and 3 cancer themes containing cancer prevention, screening, and treatment. All data in the parallel corpus are online, available for users to browse and download ( http://www.phoc.org.cn/ECCParaCorp/ ). Conclusions ECCParaCorp is a parallel corpus focused on cancer in a cross-lingual form, which is openly accessible. It would make up the imbalance of scarce multilingual corpus resources, bridge the gap between human readable information and machine understanding data resources, and would contribute to intelligent technology application as a preparatory data foundation e.g. cancer-related machine translation, cancer system development towards medical education, and disease-oriented knowledge extraction. |
topic |
Medical parallel corpus Cancer information Cross language Bilingual Cancer data HealthNLP |
url |
http://link.springer.com/article/10.1186/s12911-020-1116-1 |
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doaj-7b91fe0567994edd9b72f4553bcb45cb2020-11-25T03:01:03ZengBMCBMC Medical Informatics and Decision Making1472-69472020-07-0120S311210.1186/s12911-020-1116-1ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and applicationHetong Ma0Feihong Yang1Jiansong Ren2Ni Li3Min Dai4Xuwen Wang5An Fang6Jiao Li7Qing Qian8Jie He9Institute of Medical Information/Library, Chinese Academy of Medical Sciences and Peking Union Medical CollegeInstitute of Medical Information/Library, Chinese Academy of Medical Sciences and Peking Union Medical CollegeOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeOffice of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeInstitute of Medical Information/Library, Chinese Academy of Medical Sciences and Peking Union Medical CollegeInstitute of Medical Information/Library, Chinese Academy of Medical Sciences and Peking Union Medical CollegeInstitute of Medical Information/Library, Chinese Academy of Medical Sciences and Peking Union Medical CollegeInstitute of Medical Information/Library, Chinese Academy of Medical Sciences and Peking Union Medical CollegeDepartment of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical CollegeAbstract Background The increasing global cancer incidence corresponds to serious health impact in countries worldwide. Knowledge-powered health system in different languages would enhance clinicians’ healthcare practice, patients’ health management and public health literacy. High-quality corpus containing cancer information is the necessary foundation of cancer education. Massive non-structural information resources exist in clinical narratives, electronic health records (EHR) etc. They can only be used for training AI models after being transformed into structured corpus. However, the scarcity of multilingual cancer corpus limits the intelligent processing, such as machine translation in medical scenarios. Thus, we created the cancer specific cross-lingual corpus and open it to the public for academic use. Methods Aiming to build an English-Chinese cancer parallel corpus, we developed a workflow of seven steps including data retrieval, data parsing, data processing, corpus implementation, assessment verification, corpus release, and application. We applied the workflow to a cross-lingual, comprehensive and authoritative cancer information resource, PDQ (Physician Data Query). We constructed, validated and released the parallel corpus named as ECCParaCorp, made it openly accessible online. Results The proposed English-Chinese Cancer Parallel Corpus (ECCParaCorp) consists of 6685 aligned text pairs in Xml, Excel, Csv format, containing 5190 sentence pairs, 1083 phrase pairs and 412 word pairs, which involved information of 6 cancers including breast cancer, liver cancer, lung cancer, esophageal cancer, colorectal cancer, and stomach cancer, and 3 cancer themes containing cancer prevention, screening, and treatment. All data in the parallel corpus are online, available for users to browse and download ( http://www.phoc.org.cn/ECCParaCorp/ ). Conclusions ECCParaCorp is a parallel corpus focused on cancer in a cross-lingual form, which is openly accessible. It would make up the imbalance of scarce multilingual corpus resources, bridge the gap between human readable information and machine understanding data resources, and would contribute to intelligent technology application as a preparatory data foundation e.g. cancer-related machine translation, cancer system development towards medical education, and disease-oriented knowledge extraction.http://link.springer.com/article/10.1186/s12911-020-1116-1Medical parallel corpusCancer informationCross languageBilingualCancer dataHealthNLP |