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진단명 자동 레이블링을 위한 딥러닝기반 판독기록문으로부터 최종 진단명 추출
안경진(Kyeong-Jin Ann),장영걸(Yeonggul Jang),김세근(Sekeun Kim),심학준(Hackjoom Shim),장혁재(Hyuk-Jae Chang) 대한전자공학회 2018 대한전자공학회 학술대회 Vol.2018 No.6
A variety of studies are being conducted to solve the medical field problems that require high accuracy as well as professional anatomical knowledge by combining AI, which has been a huge success in the field of vision. However, implementing final diagnosis training data by analyzing extensive amount medical treatment record is slowing the progress of the study due to the time consuming issue. This paper proposed a combined network of CNN and RNN to automatically extract final diagnosis from medical treatment record. Also, Weights of pre-learned embedding vectors is transferred to the embedding layer in front of CNN-RNN model. This has solved the problem of performance degradation due to insufficient training data and the combination of feature maps created through parallel CNN-RNN model allows analysis between long sentences as well as between adjacent words.