Predicting Risks of Machine Translations of Public Health Resources by Developing Interpretable Machine Learning Classifiers

Predicting Risks of Machine Translations of Public Health Resources by Developing Interpretable Machine Learning Classifiers

We aimed to develop machine learning classifiers as a risk-prevention mechanism to help medical professionals with little or no knowledge of the patient’s languages in order to predict the likelihood of clinically significant mistakes or incomprehensible MT outputs based on the features of English s...

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Bibliographic Details
Main Authors: Wenxiu Xie, Meng Ji, Riliu Huang, Tianyong Hao, Chi-Yin Chow
Format: Article
Language:English
Published: MDPI AG 2021-08-01
Series:International Journal of Environmental Research and Public Health
Subjects:
multinominal naïve bayes classifier
public health education and promotion
machine learning
digital vulnerability
Online Access:https://www.mdpi.com/1660-4601/18/16/8789

Internet

https://www.mdpi.com/1660-4601/18/16/8789

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