Extracting social determinants of health from clinical note text with classification and sequence-to-sequence approaches.
J. Am. Medical Informatics Assoc., July, 2023
An Empirical Study of Clinical Note Generation from Doctor-Patient Encounters.
Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023
Deep learning approaches for extracting adverse events and indications of dietary supplements from clinical text.
J. Am. Medical Informatics Assoc., 2021
HPO2Vec+: Leveraging heterogeneous knowledge resources to enrich node embeddings for the Human Phenotype Ontology.
J. Biomed. Informatics, 2019
Normalizing Dietary Supplement Product Names Using the RxNorm Model.
Proceedings of the MEDINFO 2019: Health and Wellbeing e-Networks for All, 2019
Using natural language processing methods to classify use status of dietary supplements in clinical notes.
BMC Medical Informatics Decis. Mak., 2018
Leveraging Association Rule Mining to Detect Pathophysiological Mechanisms of Chronic Kidney Disease Complicated by Metabolic Syndrome.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018
Detecting Signals of Interactions Between Warfarin and Dietary Supplements in Electronic Health Records.
Proceedings of the MEDINFO 2017: Precision Healthcare through Informatics, 2017
Classifying Supplement Use Status in Clinical Notes.
Proceedings of the Summit on Clinical Research Informatics, 2017
Evaluating automatic methods to extract patients' supplement use from clinical reports.
Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017
Classification of use status for dietary supplements in clinical notes.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2016