Doctoral Consortium

The following student presentations have been accepted to the Doctoral Consortium.

Doctoral Consortium Poster Title Presenting Author
Towards Interactive NLP on Clinical Text: An Intelligent Signout Tool Gaurav Trivedi*, University of Pittsburgh
Application of Inertial Measurement Units for Advanced Safety Surveillance System using Individualized Sensor Technology (ASSIST): A Data Fusion and Machine Learning Approach Amir Baghdadi*, University at Buffalo
The Validity and Reliability of Social Media as a Source for Idiopathic Pulmonary Fibrosis Patient-Reported Outcomes Kim Tran*, University of Arkansas, Little Rock
The Benefits and Challenges of Utilizing Temporal Representations on Noisy Clinical Datasets Kang Lin Hsieh*, School of Biomedical Informatics at UTHSC at Houston
Identify Opioid Use Problems: Text Mining Approach Abdullah Alzeer*, IUPUI
Camera-Based Peripheral Edema Measurement Using Machine Learning Tingyu Mao*, Columbia University; Junbo Chen, Columbia University
Mental Health Analysis via Social Media Data Amir Yazdavar*, Wright state University; Mohammad Saied Mahdavinejad, Wright state University; Goonmeet Bajaj, Wright state University; Krishnaprasad Thirunarayan, Wright State University; Jyotishman Pathak, Weill Cornell Medical College; Amit Sheth, Wright state University
Mining Temporal Patterns from Sequential Healthcare Data Faezeh Movahedi*, University of Pittsburgh; Yiye Zhang, Weill Cornell Medicine; Rema Padman, Carnegie Mellon University; James Antaki, Cornell University
Predicting End-of-Life Vincent Major*, NYU Langone Medical Center; Yindalon Aphinyanaphongs, NYUMC
Architectures and Patterns for Leveraging High-Frequency Low-Fidelity Data in Healthcare Peng Zhang*, Vanderbilt University
Enabling Effective Data Interaction for Domain Experts Protiva Rahman*, The Ohio State University

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