Factuality Detection using Machine Translation -- a Use Case for German Clinical Text

• URL: http://arxiv.org/abs/2308.08827v1
• Date: Thu, 17 Aug 2023 07:24:06 GMT
• Title: Factuality Detection using Machine Translation -- a Use Case for German Clinical Text
• Authors: Mohammed Bin Sumait, Aleksandra Gabryszak, Leonhard Hennig, Roland Roller
• Abstract summary: This work presents a simple solution using machine translation to translate English data to German to train a transformer-based factuality detection model. Factuality can play an important role when automatically processing clinical text, as it makes a difference if particular symptoms are explicitly not present, possibly present, not mentioned, or affirmed.
• Score: 45.875111164923545
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Factuality can play an important role when automatically processing clinical text, as it makes a difference if particular symptoms are explicitly not present, possibly present, not mentioned, or affirmed. In most cases, a sufficient number of examples is necessary to handle such phenomena in a supervised machine learning setting. However, as clinical text might contain sensitive information, data cannot be easily shared. In the context of factuality detection, this work presents a simple solution using machine translation to translate English data to German to train a transformer-based factuality detection model.

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