no code implementations • 18 Mar 2024 • Maria Mahbub, Gregory M. Dams, Sudarshan Srinivasan, Caitlin Rizy, Ioana Danciu, Jodie Trafton, Kathryn Knight
SUD identification and treatment depend on a variety of factors such as severity, co-determinants (e. g., withdrawal symptoms), and social determinants of health.
1 code implementation • 15 May 2023 • Maria Mahbub, Ian Goethert, Ioana Danciu, Kathryn Knight, Sudarshan Srinivasan, Suzanne Tamang, Karine Rozenberg-Ben-Dror, Hugo Solares, Susana Martins, Jodie Trafton, Edmon Begoli, Gregory Peterson
We also demonstrate the QA model's ability to extract IDU-related information on temporally out-of-distribution data.
1 code implementation • 26 Feb 2022 • Maria Mahbub, Sudarshan Srinivasan, Edmon Begoli, Gregory D Peterson
We present an adversarial learning-based domain adaptation framework for the biomedical machine reading comprehension task (BioADAPT-MRC), a neural network-based method to address the discrepancies in the marginal distributions between the general and biomedical domain datasets.
no code implementations • 23 Feb 2021 • Jeremiah Duncan, Fabian Fallas, Chris Gropp, Emily Herron, Maria Mahbub, Paula Olaya, Eduardo Ponce, Tabitha K. Samuel, Daniel Schultz, Sudarshan Srinivasan, Maofeng Tang, Viktor Zenkov, Quan Zhou, Edmon Begoli
To this end, and using those established techniques, we first developed an experimental frame-work for author detection and input perturbations.