%0 Journal Article
%T A Semantic Parsing Method for Mapping Clinical Questions to Logical Forms
%A Braja Gopal Patra
%A Kirk Roberts
%J Archive of "AMIA Annual Symposium Proceedings".
%D 2017
%X This paper presents a method for converting natural language questions about structured data in the electronic health record (EHR) into logical forms. The logical forms can then subsequently be converted to EHR-dependent structured queries. The natural language processing task, known as semantic parsing, has the potential to convert questions to logical forms with extremely high precision, resulting in a system that is usable and trusted by clinicians for real-time use in clinical settings. We propose a hybrid semantic parsing method, combining rule-based methods with a machine learning-based classifier. The overall semantic parsing precision on a set of 212 questions is 95.6%. The parser¡¯s rules furthermore allow it to ¡°know what it does not know¡±, enabling the system to indicate when unknown terms prevent it from understanding the question¡¯s full logical structure. When combined with a module for converting a logical form into an EHR-dependent query, this high-precision approach allows for a question answering system to provide a user with a single, verifiably correct answer
%U https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5977685/