Oleynik M, Kugic A, Kasáč Z, Kreuzthaler M. Evaluating shallow and deep learning strategies for the 2018 n2c2 shared task on clinical text classification [Internet]. Journal of the American Medical Informatics Association 2019;26(11):1247-1254. https://doi.org/10.1093/jamia/ocz149

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 [Internet]. Journal of the American Medical Informatics Association 2018;25(3):331-336. https://doi.org/10.1093/jamia/ocx132

Luo Y, Cheng Y, Uzuner Ö, Szolovits P, Starren J. Segment convolutional neural networks (Seg-CNNs) for classifying relations in clinical notes [Internet]. Journal of the American Medical Informatics Association 2018;25(1):93-98. https://doi.org/10.1093/jamia/ocx090

Uzuner Ö, Stubbs A, Filannino M. A natural language processing challenge for clinical records: Research Domains Criteria (RDoC) for psychiatry [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S1-S3. https://doi.org/10.1016/j.jbi.2017.10.005

Stubbs A, Filannino M, Uzuner Ö. De-identification of psychiatric intake records: Overview of 2016 CEGS N-GRID shared tasks Track 1 [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S4-S18. https://doi.org/10.1016/j.jbi.2017.06.011

Lee H-J, Wu Y, Zhang Y, Xu J, Xu H, Roberts K. A hybrid approach to automatic de-identification of psychiatric notes [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S19-S27. https://doi.org/10.1016/j.jbi.2017.06.006

Dehghan A, Kovacevic A, Karystianis G, Keane JA, Nenadic G. Learning to identify Protected Health Information by integrating knowledge- and data-driven algorithms: A case study on psychiatric evaluation notes [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S28-S33. https://doi.org/10.1016/j.jbi.2017.06.005

Liu Z, Tang B, Wang X, Chen Q. De-identification of clinical notes via recurrent neural network and conditional random field [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S34-S42. https://doi.org/10.1016/j.jbi.2017.05.023

Jiang Z, Zhao C, He B, Guan Y, Jiang J. De-identification of medical records using conditional random fields and long short-term memory networks [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S43-S53. https://doi.org/10.1016/j.jbi.2017.10.003

Bui DDA, Wyatt M, Cimino JJ. The UAB Informatics Institute and 2016 CEGS N-GRID de-identification shared task challenge [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S54-S61. https://doi.org/10.1016/j.jbi.2017.05.001

Filannino M, Stubbs A, Uzuner Ö. Symptom severity prediction from neuropsychiatric clinical records: Overview of 2016 CEGS N-GRID shared tasks Track 2 [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S62-S70. https://doi.org/10.1016/j.jbi.2017.04.017

Goodwin TR, Maldonado R, Harabagiu SM. Automatic recognition of symptom severity from psychiatric evaluation records [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S71-S84. https://doi.org/10.1016/j.jbi.2017.05.020

Rios A, Kavuluru R. Ordinal convolutional neural networks for predicting RDoC positive valence psychiatric symptom severity scores [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S85-S93. https://doi.org/10.1016/j.jbi.2017.05.008

Posada JD, Barda AJ, Shi L, Xue D, Ruiz V, Kuan P-H, Ryan ND, Tsui FR. Predictive modeling for classification of positive valence system symptom severity from initial psychiatric evaluation records [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S94-S104. https://doi.org/10.1016/j.jbi.2017.05.019

Liu Y, Gu Y, Nguyen JC, Li H, Zhang J, Gao Y, Huang Y. Symptom severity classification with gradient tree boosting [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S105-S111. https://doi.org/10.1016/j.jbi.2017.05.015

Scheurwegs E, Sushil M, Tulkens S, Daelemans W, Luyckx K. Counting trees in Random Forests: Predicting symptom severity in psychiatric intake reports [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S112-S119. https://doi.org/10.1016/j.jbi.2017.06.007

Clark C, Wellner B, Davis R, Aberdeen J, Hirschman L. Automatic classification of RDoC positive valence severity with a neural network [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S120-S128. https://doi.org/10.1016/j.jbi.2017.07.005

Zhang Y, Zhang O, Wu Y, Lee H-J, Xu J, Xu H, Roberts K. Psychiatric symptom recognition without labeled data using distributional representations of phrases and on-line knowledge [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S129-S137. https://doi.org/10.1016/j.jbi.2017.06.014

Tran T, Kavuluru R. Predicting mental conditions based on "history of present illness" in psychiatric notes with deep neural networks [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S138-S148. https://doi.org/10.1016/j.jbi.2017.06.010

Dai H-J, Su EC-Y, Uddin M, Jonnagaddala J, Wu C-S, Syed-Abdul S. Exploring associations of clinical and social parameters with violent behaviors among psychiatric patients [Internet]. Journal of Biomedical Informatics 2017;75(Supplement):S149-S159. https://doi.org/10.1016/j.jbi.2017.08.009