企画の背景

More and more hospitals have moved from paper-based information management to electronic health record (EHR) system, which has enabled retrieval of massive clinical data. Clinical data is represented in structured and unstructured form. Structured data typically encodes demographics, lab values, medication lists, etc., which is easily searchable and easier to analyze. However, much of the clinically important data – signs and symptoms, symptom severity, disease status, etc. – are not provided in structured data fields, but rather are written in clinician generated narrative text. Natural language processing (NLP) provides a way for accessing this important data source, while morphological analysis for word segmentation is the first and most crucial step for Japanese NLP. It has been widely accepted that the use of dictionary can improve the performance of morphological analyzer. Several Japanese medical glossaries have been compiled by different institutions for different purposes. However, these glossaries are not developed for NLP purpose and there is a lack of centralized management of existing resources. Considering the backgrounds, we think it necessary to integrate medical terms from heterogeneous sources to create a new dictionary for the purpose of NLP in clinical settings. Our team was comprised of professionals with extensive experience in editing medical glossaries, experts in medical NLP and in web searching, also a medical doctor, and PhD students. This workshop gathered a group of researchers passionate about medical NLP, who have devoted their efforts and finally realized this purpose.