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Title |
MTReadable: Arabic Readability Corpus for Medical Tests Information |
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Author |
Dimah Alahmdi, Athir Saeed Alghamdi, Neda’a Almuallim, Suaad Alarifi |
| Citation |
Vol. 21 No. 5 pp. 84-89 |
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Abstract |
Medical tests are very important part of the health monitoring process. It is performed for various reasons like diagnosing diseases, determining medications effectiveness, etc. Due to that, patients should be able to read and understand the available online tests and results in order to take proper decisions regarding their health condition. In fact, people are varying in their educational level and health backgrounds that make providing such information in an easily readable format by the majority of people considered as a challenge in the health domain since ever. This paper describes the MTReadable corpus which constructed for evaluating the readability of online medical tests. It covered 32 basic periodic check-up tests with over 36k words. These tests information are annotated and labelled based on three readability levels which are easy, neutral and difficult by three non-specialists native Arabic speakers. This paper contributes to enriching the Arabic health research community with an investigation of the level of readability of online medical tests and to be a baseline for further complex health online reports and information. |
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Keywords |
Text mining, Arabic corpus, Readability corpus, Medical Test |
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URL |
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|
Title |
MTReadable: Arabic Readability Corpus for Medical Tests Information |
|
Author |
Dimah Alahmdi, Athir Saeed Alghamdi, Neda’a Almuallim, Suaad Alarifi |
| Citation |
Vol. 21 No. 5 pp. 84-89 |
|
Abstract |
Medical tests are very important part of the health monitoring process. It is performed for various reasons like diagnosing diseases, determining medications effectiveness, etc. Due to that, patients should be able to read and understand the available online tests and results in order to take proper decisions regarding their health condition. In fact, people are varying in their educational level and health backgrounds that make providing such information in an easily readable format by the majority of people considered as a challenge in the health domain since ever. This paper describes the MTReadable corpus which constructed for evaluating the readability of online medical tests. It covered 32 basic periodic check-up tests with over 36k words. These tests information are annotated and labelled based on three readability levels which are easy, neutral and difficult by three non-specialists native Arabic speakers. This paper contributes to enriching the Arabic health research community with an investigation of the level of readability of online medical tests and to be a baseline for further complex health online reports and information. |
|
Keywords |
Text mining, Arabic corpus, Readability corpus, Medical Test |
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URL |
