If your question is not listed below, email Martin Krallinger to encargo-pln-life@bsc.es or Salvador Lima López to salvador.limalopez@gmail.com.
Q: What is the goal of the shared task?
The goal is, given a collection of clinical reports, to detect occupations mentions and classify them into professions or employment statuses (Track 1), detect who they are referring to (Track 2) and normalize them (Track 3).
Q: Why should I participate?
Demographic information about patients may reveal key aspects for the diagnosis and treatment of their condition. Professions and employment situations are a good example of demographic variables, and are usually only found in unstructured text. The COVID-19 pandemic has highlighted the relevance of occupations at high risk of contagion such as nurses, doctors, hospital cleaners and shopkeepers and of impact on mental health such as health-workers, retired people and the unemployed. Finding these variables facilitates clustering of patients in risk groups and the implementation of the most suitable treatment and preventive measures.
Q: How do I register?
Fill in the following form: https://docs.google.com/forms/d/e/1FAIpQLSclQgJKfqKZgV3M94VQbKcLpqs3OFw66ZuA84Mjz3aYvD3XrA/viewform
Q: How do I submit the results?
See the Submission page for more info.
Q: Can I use additional training data to improve model performance?
Yes, participants may use any additional training data they have available, as long as they describe it in the working notes. We will ask to summarize such resources in your participant paper.
Q: MEDDOPROF has three tracks. Do I need to participate in all of them?
Sub-tracks are independent and participants may participate in one or two of them.
Q: Which controlled vocabularies are used for normalization?
Both the European Skills, Competences, Qualifications and Occupations (ESCO) classification and SNOMED-CT are used for normalization. With some exceptions, professions are generally mapped to ESCO and employment statuses are mapped to SNOMED-CT.