Druginformer desires to construct a community of participants interested in understanding how medicine can effect the human body. Our team of scientists and engineers have created a system that scours the web for potential adverse events and aggregates this content into reports for interested consumers. We hope that these reports are useful -- whether you are a med user struggling with a side effect, or a doctor trying to select the best medicine for your patient, or even just a curious consumer.
Druginformer can be made even better with your help.
The system for recognizing and extracting adverse events uses state of the art machine learning algorithms to identify genuine adverse event reports buried in user comments. These classification tools require human labels to improve performance. The more labels the better. If you are interested in taking some time to label content, please create a new account, and access our labeling interface. There is no obligation to label with a new account, we only require you are logged in so that we can map your labels to your user id. Any time you spend labeling will help improve our classification techniques and allow us to build even better reports.
When you have registered click "Sign In" at the top right of the screen to user your new username and password to sign in. Once you are logged in, explore our "Workbench" or click "Access Labeler" to help us label adverse events in social media.