2018 (2 Tracks)

Uzuner Ö, Stubbs A, Lenert L. Advancing the state of the art in automatic extraction of adverse drug events from narratives.

Stubbs A, Uzuner Ö. New approaches to cohort selection.

Stubbs A, Filannino M, Soysal E, Henry S, Uzuner Ö. Cohort selection for clinical trials: n2c2 2018 shared task track 1.

Vydiswaran VV, Strayhorn A, Zhao X, Robinson P, Agarwal M, Bagazinski E, Essiet M, Iott B, Joo H, Ko P, Lee D, Lu JX, Liu J, Murali A, Sasagawa K, Wang T, Yuan N. Hybrid bag of approaches to characterize selection criteria for cohort identification.

Segura-Bedmar I, Raez P. Cohort selection for clinical trials using deep learning models.

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.

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.

Xiong Y, Shi X, Chen S, Jiang D, Tang B, Wang X, Chen Q, Yan J. Cohort selection for clinical trials using hierarchical neural network.

Ju M, Nguyen N, Miwa M, Ananiadou S. An ensemble of neural models for nested adverse drug events and medication extraction with subwords.

Chen L, Gu Y, Ji X, Lou C, Sun Z, Li H, Gao Y, Huang Y. Clinical trial cohort selection based on multi-level rule-based natural language processing system.