---
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**) e**x**traction 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](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 <ADE>"*. 

## How to use

```python

```