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141 results

141 results

2020

Henry S, Buchan K, Filannino M, Stubbs A, Uzuner Ö. 2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records.
Journal of the American Medical Informatics Association. 2020;27(1):3–12.
Henry S, Buchan K, Filannino M, Stubbs A, Uzuner Ö. 2018 n2c2 shared task on adverse drug events and medication extraction in electronic health records.
Journal of the American Medical Informatics Association. 2020;27(1):3–12.
Alimova I, Tutubalina E. Multiple features for clinical relation extraction: A machine learning approach.
Journal of Biomedical Informatics. 2020;103.
Alimova I, Tutubalina E. Multiple features for clinical relation extraction: A machine learning approach.
Journal of Biomedical Informatics. 2020;103.
Wei Q, Ji Z, Li Z, Du J, Wang J, Xu J, Xiang Y, Tiryaki F, Wu S, Zhang Y, Tao C, Xu H. A study of deep learning approaches for medication and adverse drug event extraction from clinical text.
Journal of the American Medical Informatics Association. 2020;27(1):13–21.
Wei Q, Ji Z, Li Z, Du J, Wang J, Xu J, Xiang Y, Tiryaki F, Wu S, Zhang Y, Tao C, Xu H. A study of deep learning approaches for medication and adverse drug event extraction from clinical text.
Journal of the American Medical Informatics Association. 2020;27(1):13–21.
Yang X, Bian J, Fang R, Bjarnadottir R, Hogan W, Wu Y. Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting.
Journal of the American Medical Informatics Association. 2020;27(1):65–72.
Yang X, Bian J, Fang R, Bjarnadottir R, Hogan W, Wu Y. Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting.
Journal of the American Medical Informatics Association. 2020;27(1):65–72.
Kim Y, Meystre S. Ensemble method–based extraction of medication and related information from clinical texts.
Journal of the American Medical Informatics Association. 2020;27(1):31–38.
Kim Y, Meystre S. Ensemble method–based extraction of medication and related information from clinical texts.
Journal of the American Medical Informatics Association. 2020;27(1):31–38.
Ju M, Nguyen N, Miwa M, Ananiadou S. An ensemble of neural models for nested adverse drug events and medication extraction with subwords.
Journal of the American Medical Informatics Association. 2020;27(1):22–30.
Ju M, Nguyen N, Miwa M, Ananiadou S. An ensemble of neural models for nested adverse drug events and medication extraction with subwords.
Journal of the American Medical Informatics Association. 2020;27(1):22–30.
Christopoulou F, Tran TT, Sahu SK, Miwa M, Ananiadou S. Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.
Journal of the American Medical Informatics Association. 2020;27(1):39–46.
Christopoulou F, Tran TT, Sahu SK, Miwa M, Ananiadou S. Adverse drug events and medication relation extraction in electronic health records with ensemble deep learning methods.
Journal of the American Medical Informatics Association. 2020;27(1):39–46.
Uzuner Ö, Stubbs A, Lenert L. Advancing the state of the art in automatic extraction of adverse drug events from narratives.
Journal of the American Medical Informatics Association. 2020;27(1).
Uzuner Ö, Stubbs A, Lenert L. Advancing the state of the art in automatic extraction of adverse drug events from narratives.
Journal of the American Medical Informatics Association. 2020;27(1).
Dai HJ, Su CH, Wu CS. Adverse drug event and medication extraction in electronic health records via a cascading architecture with different sequence labeling models and word embeddings.
Journal of the American Medical Informatics Association. 2020;27(1):47–55.
Dai HJ, Su CH, Wu CS. Adverse drug event and medication extraction in electronic health records via a cascading architecture with different sequence labeling models and word embeddings.
Journal of the American Medical Informatics Association. 2020;27(1):47–55.
Chen L, Gu Y, Ji X, Sun Z, Li H, Gao Y, Huang Y. Extracting medications and associated adverse drug events using a natural language processing system combining knowledge base and deep learning.
Journal of the American Medical Informatics Association. 2020;27(1):56–64.
Chen L, Gu Y, Ji X, Sun Z, Li H, Gao Y, Huang Y. Extracting medications and associated adverse drug events using a natural language processing system combining knowledge base and deep learning.
Journal of the American Medical Informatics Association. 2020;27(1):56–64.

2019

Oleynik M, Kugic A, Kasáč Z, Kreuzthaler M. Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification.
Journal of the American Medical Informatics Association. 2019;26(11):1247–1254.
Oleynik M, Kugic A, Kasáč Z, Kreuzthaler M. Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification.
Journal of the American Medical Informatics Association. 2019;26(11):1247–1254.
Stubbs A, Filannino M, Soysal E, Henry S, Uzuner Ö. Cohort selection for clinical trials: n2c2 2018 shared task track 1.
Journal of the American Medical Informatics Association. 2019;26(11):1163–1171.
Stubbs A, Filannino M, Soysal E, Henry S, Uzuner Ö. Cohort selection for clinical trials: n2c2 2018 shared task track 1.
Journal of the American Medical Informatics Association. 2019;26(11):1163–1171.