no code implementations • 18 May 2022 • Jingqing Zhang, Atri Sharma, Luis Bolanos, Tong Li, Ashwani Tanwar, Vibhor Gupta, Yike Guo
This paper proposes a scalable workflow which leverages both structured data and unstructured textual notes from EHRs with techniques including NLP, AutoML and Clinician-in-the-Loop mechanism to build machine learning classifiers to identify patients at scale with given diseases, especially those who might currently be miscoded or missed by ICD codes.