license: mit
tags:
- adverse-drug-events
- twitter
- social-media-mining-for-health
- SMM4H
widget:
- text: >-
Did the patient suffer from a side effect?: weird thing about paxil:
feeling fully awake and energized and feeling completely tired and
half-asleep at the same time
example_title: Adverse Drug Event Extraction
t2t-adeX-prompt
t2t-adeX-prompt is a text-to-text (t2t) adverse drug event (ade) extraction model trained with prompting English tweets reporting adverse drug events. It is trained as part of BOUN-TABI system for the Social Media Mining for Health (SMM4H) 2022 shared task. The system description paper has been accepted for publication in Proceedings of the Seventh Social Media Mining for Health (#SMM4H) Workshop and Shared Task and will be available soon. The source code has been released on GitHub at https://github.com/gokceuludogan/boun-tabi-smm4h22.
The model utilizes the T5 model and its text-to-text formulation. The inputs are fed to the model with the prompt "Did the patient suffer from a side effect?" while the outputs uses the template "Yes, the patient suffered from ".
How to use