Publications

Sort & Filters

Filters

Challenges

141 results

141 results

2019

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.
Journal of the American Medical Informatics Association. 2019;26(11):1218–1226.
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.
Journal of the American Medical Informatics Association. 2019;26(11):1218–1226.
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.
Journal of the American Medical Informatics Association. 2019;26(11):1172–1180.
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.
Journal of the American Medical Informatics Association. 2019;26(11):1172–1180.
Chen CJ, Warikoo N, Chang YC, Chen JH, Hsu WL. Medical knowledge infused convolutional neural networks for cohort selection in clinical trials.
Journal of the American Medical Informatics Association. 2019;26(11):1227–1236.
Chen CJ, Warikoo N, Chang YC, Chen JH, Hsu WL. Medical knowledge infused convolutional neural networks for cohort selection in clinical trials.
Journal of the American Medical Informatics Association. 2019;26(11):1227–1236.
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.
Journal of the American Medical Informatics Association. 2019;26(11):1203–1208.
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.
Journal of the American Medical Informatics Association. 2019;26(11):1203–1208.
Segura-Bedmar I, Raez P. Cohort selection for clinical trials using deep learning models.
Journal of the American Medical Informatics Association. 2019;26(11):1181–1188.
Segura-Bedmar I, Raez P. Cohort selection for clinical trials using deep learning models.
Journal of the American Medical Informatics Association. 2019;26(11):1181–1188.
Stubbs A, Uzuner Ö. New approaches to cohort selection.
Journal of the American Medical Informatics Association. 2019;26(11):1161–1162.
Stubbs A, Uzuner Ö. New approaches to cohort selection.
Journal of the American Medical Informatics Association. 2019;26(11):1161–1162.
Si Y, Wang J, Xu H, Roberts K. Enhancing clinical concept extraction with contextual embeddings .
Journal of the American Medical Informatics Association. 2019;26(11):1297–1304.
Si Y, Wang J, Xu H, Roberts K. Enhancing clinical concept extraction with contextual embeddings .
Journal of the American Medical Informatics Association. 2019;26(11):1297–1304.
Li F, Yu H. An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models .
Journal of the American Medical Informatics Association. 2019;26(7):646–654.
Li F, Yu H. An investigation of single-domain and multidomain medication and adverse drug event relation extraction from electronic health record notes using advanced deep learning models .
Journal of the American Medical Informatics Association. 2019;26(7):646–654.
Li Y, Jin R, Luo Y. Classifying relations in clinical narratives using segment graph convolutional and recurrent neural networks (Seg-GCRNs).
Journal of the American Medical Informatics Association. 2019;26(3):262–268.
Li Y, Jin R, Luo Y. Classifying relations in clinical narratives using segment graph convolutional and recurrent neural networks (Seg-GCRNs).
Journal of the American Medical Informatics Association. 2019;26(3):262–268.

2018

Luo Y, Cheng Y, Uzuner Ö, Szolovits P, Starren J. Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.
Journal of the American Medical Informatics Association. 2018;25(1):93–98.
Luo Y, Cheng Y, Uzuner Ö, Szolovits P, Starren J. Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes.
Journal of the American Medical Informatics Association. 2018;25(1):93–98.
Soysal E, Wang J, Jiang M, Wu Y, Pakhomov S, Liu H, Xu H. CLAMP – a toolkit for efficiently building customized clinical natural language processing pipelines.
Journal of the American Medical Informatics Association. 2018;25(3):331–336.
Soysal E, Wang J, Jiang M, Wu Y, Pakhomov S, Liu H, Xu H. CLAMP – a toolkit for efficiently building customized clinical natural language processing pipelines.
Journal of the American Medical Informatics Association. 2018;25(3):331–336.

2017

Stubbs A, Filannino M, Uzuner Ö. De-identification of psychiatric intake records: Overview of 2016 CEGS N-GRID shared tasks Track 1.
Journal of Biomedical Informatics. 2017;75(Supplement):S4-S18.
Stubbs A, Filannino M, Uzuner Ö. De-identification of psychiatric intake records: Overview of 2016 CEGS N-GRID shared tasks Track 1.
Journal of Biomedical Informatics. 2017;75(Supplement):S4-S18.