NLP Challenge for Detecting Medication and Adverse Drug Events from Electronic Health Records (MADE 1.0)

In this topical collection (6 articles)

1. Editorial

   Towards Drug Safety Surveillance and Pharmacovigilance: Current Progress in Detecting Medication and Adverse Drug Events from Electronic Health Records

   Feifan Liu, Abhyuday Jagannatha, Hong Yu Pages 95-97

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2. Original Research Article

   Overview of the First Natural Language Processing Challenge for Extracting Medication, Indication, and Adverse Drug Events from Electronic Health Record Notes (MADE 1.0)

   Abhyuday Jagannatha, Feifan Liu, Weisong Liu, Hong Yu Pages 99-111

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3. Original Research Article

   Adverse Drug Event Detection from Electronic Health Records Using Hierarchical Recurrent Neural Networks with Dual-Level Embedding

   Susmitha Wunnava, Xiao Qin, Tabassum Kakar, Cansu Sen, Elke A. Rundensteiner… Pages 113-122

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4. Original Research Article

   MADEx: A System for Detecting Medications, Adverse Drug Events, and Their Relations from Clinical Notes

   Xi Yang, Jiang Bian, Yan Gong, William R. Hogan, Yonghui Wu Pages 123-133

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5. Original Research Article

   Adverse Drug Events Detection in Clinical Notes by Jointly Modeling Entities and Relations Using Neural Networks

   Bharath Dandala, Venkata Joopudi, Murthy Devarakonda Pages 135-146

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6. Original Research Article

   Detecting Adverse Drug Events with Rapidly Trained Classification Models

   Alec B. Chapman, Kelly S. Peterson, Patrick R. Alba, Scott L. DuVall… Pages 147-156

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