MEDIQA-SYNUR @ ClinicalNLP 2026

Observation Extraction from Nurse Dictations

Task & Data

Registration, Datasets & Evaluation

Task & Data

This shared task presents the first community challenge centered on nursing data, aimed at advancing methods for clinical documentation. The goal is to reduce nursing burden and improve the accuracy and completeness of patient records by automatically capturing clinically salient information from nurse-patient conversations. The task focuses on extracting and normalizing clinical observations from conversational transcripts and mapping them to a large ontology of clinical concepts.

We recently introduced SYNUR, the first dataset designed for observation extraction in nursing dictations [1]. Building on this resource, we extend the MEDIQA-OE 2025 shared task [2] to address the unique challenges posed by nurse transcriptions.

For the test phase, participants will be evaluated on a curated and validated benchmark of nurse dictations generated through a controlled multi-agent simulation pipeline. Gold-standard annotations were produced by expert nurses using an open-source, large-scale clinical ontology, ensuring high annotation quality and clinical relevance.

References:

[1] Empowering Healthcare Practitioners with Language Models: Structuring Speech Transcripts in Two Real-World Clinical Applications. Jean-Philippe Corbeil, Asma Ben Abacha, George Michalopoulos, Phillip Swazinna, Miguel A. del Agua, Jérôme Tremblay, Akila Jeeson Daniel, Cari Bader, Yu-Cheng Cho, Pooja Krishnan, Nathan Bodenstab, Thomas Lin, Wenxuan Teng, François Beaulieu, Paul Vozila. CoRR abs/2507.05517 (2025)

[2] Overview of the MEDIQA-OE 2025 Shared Task on Medical Order Extraction from Doctor-Patient Consultations. Jean-Philippe Corbeil, Asma Ben Abacha, Jérôme Tremblay, Phillip Swazinna, Akila Jeeson Daniel, Miguel A. del Agua, François Beaulieu. CoRR abs/2510.26974 (2025)

Registration, Datasets & Evaluation

Registration:

Step 1: Please fill out the MEDIQA-SYNUR 2026 registration form at the following link: https://forms.gle/LKeKsuu6iea53mwHA

If you are unable to access the registration form, please email us at mediqa.organizers@gmail.com with the following information: {first name, last name, team name, affiliation, country/countries of affiliation, codabench username (for run submission), github username (for code submission)}
The registration must be submitted by the team lead or representative (please do not submit multiple registrations from the same team).

Step 2: After submitting the registration form, please review and accept the Terms, and join the Codabench competition using the following link: https://www.codabench.org/competitions/12113/ (You can find the Terms under the Terms page on Codabench).

Data & Evaluation:

Once both your registration form and your Codabench request have been approved, you will receive access to: The dataset & leaderboard on Codabench.

Schedule

All deadlines are 11:59PM UTC-12:00 (anywhere on Earth)

First CFP & Registration opens: Mon 8 Dec 2025
Development data release: Mon 15 Dec 2025
Registration ends: Fri 30 Jan 2026
Test data release: Mon 02 Feb 2026
Run (& code) submission due: Thu 05 Feb 2026
Release of the results by the organizers: Fri 06 Feb 2026
Paper submission due: Fri 13 Feb 2026
Notification of acceptance: Wed 11 Mar 2026
Final version due: Mon 30 Mar 2026
ClinicalNLP Workshop: Saturday 16 May 2026, Palma de Mallorca, Spain

Contact

If you have any questions regarding your team's registration, please email us at mediqa.organizers@gmail.com
For more updates or inquiries, join the MEDIQA Google group https://groups.google.com/g/mediqa-nlp and email us at mediqa-nlp@googlegroups.com (mailing list)

Organizers

Asma Ben Abacha, Microsoft, USA
Nate Bodenstab, Microsoft, USA
Jean-Philippe Corbeil, Microsoft, Canada
George Michalopoulos, Microsoft, Canada

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