MARAS: Signaling Multi-Drug Adverse Reactions. - Xiao Qin 003; Tabassum Kakar; Susmitha Wunnava; Elke A. Rundensteiner; Lei Cao 004 (KDD, 2017)

Towards transforming FDA adverse event narratives into actionable structured data for improved pharmacovigilance. - Susmitha Wunnava; Xiao Qin 003; Tabassum Kakar; Vimig Socrates; Amber Wallace; Elke A. Rundensteiner (SAC, 2017)

Deep Learning Strategies for Automatic Detection of Medication and Adverse Drug Events from Electronic Health Records. - Susmitha Wunnava; Xiao Qin 003; Tabassum Kakar; Elke A. Rundensteiner; Xiangnan Kong (AMIA, 2018)

One Size Does Not Fit All: An Ensemble Approach Towards Information Extraction from Adverse Drug Event Narratives. - Susmitha Wunnava; Xiao Qin 003; Tabassum Kakar; Xiangnan Kong; Elke A. Rundensteiner; Sanjay K. Sahoo; Suranjan De (HEALTHINF, 2018)

Multi-layered Learning for Information Extraction from Adverse Drug Event Narratives. - Susmitha Wunnava; Xiao Qin 003; Tabassum Kakar; M. L. Tlachac; Xiangnan Kong; Elke A. Rundensteiner; Sanjay K. Sahoo; Suranjan De (BIOSTEC (Selected Papers), 2018)

MeDIAR: Multi-Drug Adverse Reactions Analytics. - Xiao Qin 003; Tabassum Kakar; Susmitha Wunnava; Brian McCarthy; Andrew Schade; Huy Quoc Tran; Brian Zylich; Elke A. Rundensteiner; Lane Harrison; Sanjay K. Sahoo; Suranjan De (ICDE, 2018)

Bidirectional LSTM-CRF for Adverse Drug Event Tagging in Electronic Health Records. - Susmitha Wunnava; Xiao Qin 003; Tabassum Kakar; Elke A. Rundensteiner; Xiangnan Kong (Medication and Adverse Drug Event Detection, 2018)

Supervised Topic Compositional Neural Language Model for Clinical Narrative Understanding. - Xiao Qin 003; Cao Xiao; Tengfei Ma 001; Tabassum Kakar; Susmitha Wunnava; Xiangnan Kong; Elke A. Rundensteiner; Fei Wang 001 (IEEE BigData, 2020)

A Dual-Attention Network for Joint Named Entity Recognition and Sentence Classification of Adverse Drug Events. - Susmitha Wunnava; Xiao Qin 003; Tabassum Kakar; Xiangnan Kong; Elke A. Rundensteiner (EMNLP (Findings), 2020)