Clinical Natural Language Processing for Japanese: Challenges and Opportunities

Deep Learning (DL) has become a popular method in various industries to support human decision-making in areas such as gaming, news, finance, biology, medicine, and engineering. Although statistical learning has been used in clinical decision support for some time, deep learning has not been widely implemented in the clinical field, apart from image-related tasks. Clinical natural language processing (NLP) in decision support systems continues to rely mostly on rule-based or statistical solutions, unlike other domains that have adopted deep learning. The development of clinical NLP applications in languages other than English, such as Japanese, is still lagging behind. This paper offers a review on the challenges that deep learning faces in clinical NLP and explores potentials and opportunities in the field. The purpose is to provide a broad understanding of the clinical NLP landscape for deep learning researchers and inspire them to get involved in this field.