As a guest user you are not logged in or recognized by your IP address. You have
access to the Front Matter, Abstracts, Author Index, Subject Index and the full
text of Open Access publications.
Automated coding and classification systems play a role in healthcare for quality of care. Our objective was to predict diagnosis code from medication list of electronic medical record (EMR) using convolutional neural network (CNN). We collected the clinical note from outpatient department (OPD) of Wanfang hospital, Taiwan of 2016 and used three physicians from three departments. The dataset was split into two parts, 90% for training and 10% for test cases. We used medication list as input and International Statistical Classification of Diseases 10 (ICD 10) code as output. After data preprocess, we used word2vector CNN to predict ICD 10 code. This study shows all the three physicians from three departments achieved better performance. The best performance of model was a physician from cardiology department achieved precision 69%, recall 89% and F measure 78%. We need to include more component such as text data, lab report for evaluation.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.
This website uses cookies
We use cookies to provide you with the best possible experience. They also allow us to analyze user behavior in order to constantly improve the website for you. Info about the privacy policy of IOS Press.