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BMC Medical Informatics and Decision Making
Published in: BMC Medical Informatics and Decision Making 3/2020

Open Access 01-07-2020 | Research

ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application

Authors: Hetong Ma, Feihong Yang, Jiansong Ren, Ni Li, Min Dai, Xuwen Wang, An Fang, Jiao Li, Qing Qian, Jie He

Published in: BMC Medical Informatics and Decision Making | Special Issue 3/2020

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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.
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Metadata
Title
ECCParaCorp: a cross-lingual parallel corpus towards cancer education, dissemination and application
Authors
Hetong Ma
Feihong Yang
Jiansong Ren
Ni Li
Min Dai
Xuwen Wang
An Fang
Jiao Li
Qing Qian
Jie He
Publication date
01-07-2020
Publisher
BioMed Central
DOI
https://doi.org/10.1186/s12911-020-1116-1

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