Incorporating Knowledge Resources to Enhance Medical Information Extraction

Yasuhide Miura, Tomoko Ohkuma, Hiroshi Masuichi, Emiko Yamada Shinohara, Eiji Aramaki, Kazuhiko Ohe

Abstract: This paper describes a method to extract medical information from texts. The method targets to extract complaints and diagnoses from electronic health record texts. Complaints and diagnoses are fundamental information and can be used for more complex medical tasks. The method utilizes several medical knowledge resources to enhance the performance of extraction. With an evaluation using NTCIR10 MedNLP data, our method marked 86.53 in F1 score with a cross validation. The score is comparable to top scoring teams in NTCIR-10 MedNLP task. The approach taken to incorporate knowledge resources has a high generality. It is not restricted to the resources presented in this paper and can be applied to various other resources.