(Apologies for cross-posting)
CFP MultiCardioNER (CLEF/BioASQ 2024): Clinical Named Entity Recognition adaptation shared task (multilingual & cardiology)
https://temu.bsc.es/multicardioner/
The MultiCardioNER track focuses on the adaptation of clinical NER systems to specific high impact clinical application domains (cardiovascular diseases, the leading cause of death globally) as well as to multiple languages (English, Spanish and Italian), focusing on two clinical entity types: diseases and medications.
Key information:
· Web: https://temu.bsc.es/multicardioner
· Data: https://zenodo.org/records/10948355
· BioASQ web: http://bioasq.org/
· Registration: https://temu.bsc.es/multicardioner/registration/
Motivation
The
extraction of clinical variables from medical content is key to enable efficient healthcare data analytics. Due to the highly specialized medical language, with
considerable variation depending on the medical discipline, more specialized automatic semantic
annotation resources are needed, not only for English but also other languages.
This is particularly true for clinical content related to cardiovascular diseases (CVDs), which represent the leading cause of death globally, responsible for approximately 17.9 million deaths/year.
The MultiCardioNER task will focus on the automatic recognition of two key clinical variables or concept types, namely diseases and medications in cardiology clinical case documents with the following two aims:
· Adaptation of general clinical concept recognition systems to cardiology case reports to assess and determine how well such systems can be adapted to high impact clinical application domains / specialties (cardiology disease NER - CardioDis subtrack: Spanish).
· Promote the comparative assessment and development of clinical entity recognition systems for multiple languages (i.e., medication mention detection) as well as adaptation to specific medical specialties (MultiDrug subtrack: English, Spanish and Italian)
To enable the adaptation of general medical NER systems for diseases and medications the MultiCardioNER task will rely on a training collection of 1000 general clinical case reports in Spanish annotated with diseases (Spanish) and medications (English, Spanish and Italian).
Moreover, to be able to adapt such general medical NER approaches to cardiology case reports a development set of 250 cardiology cases will be released. The test set will consist of an additional test collection of 250 cardiology case reports.
The evaluation of systems for this task will use flat evaluation, mainly micro-averaged Precision, Recall and F-measure (MiF).
Sub-tracks:
Subtask 1 (CardioDis): Spanish adaptation of disease recognition systems to the cardiology domain
Subtask 2 (MultiDrug): Multilingual (Spanish, English and
Italian) adaptation of medication recognition systems to the cardiology domain
Tentative schedule
· MultiCardioNER Train+Dev Set Release April 9th, 2024
· MultiCardioNER Annotation Guidelines Release April 17th, 2024
· MultiCardioNER Gazetteer Release April 17th, 2024
· MultiCardioNER Test Set Texts Release May 2nd, 2024
· Participant Test Predictions Deadline
· May 15th, 2024
· Participant Evaluation Result Release May 19th, 2024
· Submission of Participant Papers Deadline May 31st, 2024
· Notification of Acceptance of Participant Papers June 24th, 2024
· Submission of Camera-ready Participant Papers Deadline July 8th, 2024
· BioASQ @ CLEF2024 September 9th-12th, 2024
Publications & conference
Following previous BioASQ/CLEF efforts, participating teams will be invited to contribute a short systems description paper for the CLEF 2024 proceedings, and to give a short presentation of their approach at the BioASQ workshop at the CLEF 2024 conference (September 09-12, 2024, in Grenoble, France)
The MultiCardioNER
Organizers & collaborators:
(Apologies for cross-posting)
Final CFP MultiCardioNER (CLEF/BioASQ 2024): Clinical Named Entity Recognition adaptation shared task (multilingual & cardiology)
https://temu.bsc.es/multicardioner/
The MultiCardioNER track focuses on the adaptation of clinical NER systems to specific high impact clinical application domains (cardiovascular diseases, the leading cause of death globally) as well as to multiple languages (English, Spanish and Italian), focusing on two clinical entity types: diseases and medications.
Key information: