Tasks:

• Task 1 - b: Biomedical Semantic Question Answering

  Benchmark datasets of biomedical questions, in English, along with gold standard (reference) answers constructed by a team of biomedical experts. The participants have to respond with relevant articles, and snippets from designated resources, as well as exact and ""ideal"" answers.

• Task 2 - Synergy: Question Answering for developing problems

  Biomedical experts pose unanswered questions for developing problems, such as COVID-19, receive the responses provided by the participating systems, and provide feedback, together with updated questions in an iterative procedure that aims to facilitate the incremental understanding of developing problems in biomedicine and public health.

• Task 3 - MultiClinSum: Multilingual Clinical Summarization

  A shared task on the automatic summarization of lengthy clinical case reports written in different languages. The organizers distribute lengthy clinical case reports written in English, Spanish, French, and Portuguese. The participants generate summaries of the clinical case reports. The evaluation is based on a comparison with manual summaries of the clinical case reports.

• Task 4 - BioNNE-L: Nested Named Entity Linking in Russian and English

  A shared task on NLP challenges in entity linking, also known as medical concept normalization (MCN), for English and Russian languages. The train/dev datasets include annotated mentions of disorders, anatomical structures, and chemicals. The participants normalize the entity mentions to concept names and unique UMLS identifiers. The evaluation is based on a comparison with manual nested named entity linking annotations.

• Task 5 - ElCardioCC: Clinical Coding in Cardiology

  The ELCardioCC on the automated clinical coding concerns i) the assignment of cardiology-related ICD-10 codes to discharge letters from Greek hospitals, ii) the extraction of the specific mentions of ICD-10 codes from the discharge letters. The evaluation is based on metrics, such as micro and macro F-measure for subtask (i) and token F-measure for subtask (ii).

• Task 6 - GutBrainIE: Gut-Brain Interplay Information Extraction

  The GutBrainIE task aims to foster the development of Information Extraction (IE) systems that support experts by automatically extracting and linking knowledge from scientific literature, facilitating the understanding of gut-brain interplay and its role in neurological disease. The task is divided into two subtasks: i) extraction of named entities and linking them to concepts in a reference ontology, and ii) identifying binary relations between entity pairs.