MRE is to establish medical-related relations (e.g., induce relation) among clinical concepts (e.g., drugs, adverse events). MRE is usually approached as a classification problem—identify pairs of concepts with valid relations and classify the relation type. Various machine learning-based classifiers such as support vector machines (SVMs), random forests (RF), and gradient boosting trees (GBT)41 have been applied. With the emergence of deep learning models, researchers have explored the long-short-term memory (LSTM) architecture for RE in both general and clinical domains52,53. Most recently, several studies adopted the BERT architecture and demonstrated superior performance for MRE on various datasets54,55,56,57,58,59.
This uses machine learning algorithms that improve over time and help each person understand the conversation. Were responsible for the overall design, development, and evaluation of this study. Had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Did the bulk of the writing, E.A.S., D.A.M., T.M., C.A.H., A.B.C., and G.L. All authors reviewed the manuscript critically for scientific content, and all authors gave final approval of the manuscript for publication.
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We had to keep going back and forth with the bot to get something coherent and properly formatted.
