ICD-10 Auto-coding System Using Deep Learning

In this research, we aim to construct an automatic ICD-10 coding system.ICD-10 is a medical classification standard which is strongly related to scope of payment in health insurance.However, the work of ICD-10 coding is time-consuming and tedious to ICD coders.Therefore, we build an ICD-10 coding system based on NLP approach to reduce their workload.The result of f1-score in whole label prediction task is up to 0.67 and 0.58 in CM and PCS, respectively.In addition, recall@20 in whole label prediction task is up to 0.87 and 0.81 in CM and PCS, respectively.In the future, we will keep working on combining the current work with the rule-based coding system and applying the other brand new NLP techniques to improve our performance.