Challenge: a tool for mapping identifiers between clinical ontologies and lexical resources is available.
Approach: They propose a tool for mapping identifiers between clinical ontologies and lexical resources.
Outcome: The proposed mapping tool can be used to enrich existing annotated corpora in multiple languages.

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Cross-Lingual Knowledge Transfer for Clinical Phenotyping (2022.lrec-1)

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Challenge: Current models for clinical phenotyping are limited to clinical notes written in English due to the large amount of labeled and unlabeled clinical text resources.
Approach: They propose to use translation-based methods with domain-specific encoders and cross-lingual encoder plus adapters to perform this task for clinics that do not use the English language.
Outcome: The proposed strategies outperform the state-of-the-art models for clinics that do not use the English language and have a small amount of in-domain data available.
A Framework for Flexible Extraction of Clinical Event Contextual Properties from Electronic Health Records (2025.acl-industry)

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Challenge: EHRs contain vast amounts of valuable clinical data, stored as unstructured text.
Approach: They propose a method that uses existing NER+L methods to classify medical entities at scale using a named entity recognition and linking task.
Outcome: The proposed model outperforms Bi-LSTM in minority class tasks with up to 28% of the time and 32% faster training time.
Annotation Interoperability for the Post-ISOCat Era (2020.lrec-1)

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Challenge: Using ISOCat successor solutions, annotation standards have been developed since 2010 .
Approach: They describe ISOCat successor solutions and annotation standardization efforts since 2010 . they describe low-cost harmonization of post-ISOCat vocabularies by means of linked ontologies .
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Biomedical term normalization of EHRs with UMLS (L18-1)

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Challenge: Currently, there is no tool for this language and for this specific purpose.
Approach: They propose a multilingual and cross-lingual tool that searches for biomedical terms in clinical texts with the Unified Medical Language System (UMLS) Metathesaurus.
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Similarity Measures for the Detection of Clinical Conditions with Verbal Fluency Tasks (N18-2)

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Challenge: Semantic Verbal Fluency tests have been used in the diagnosis of certain clinical conditions, like Dementia.
Approach: They investigate three similarity measures for automatically identifying switches in semantic chains: semantic similarity from a manually constructed resource, word association strength and semantic relatedness, both calculated from corpora.
Outcome: The proposed classifiers outperform those that use a gold standard taxonomy for clinical conditions.
Medical Crossing: a Cross-lingual Evaluation of Clinical Entity Linking (2022.lrec-1)

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Challenge: Existing approaches to medical entity linking are limited in terms of data volume and languages.
Approach: They propose to use clinical reports, clinical guidelines, and medical research papers to evaluate cross-lingual medical entity linking.
Outcome: The proposed model outperforms existing models on clinical reports, clinical guidelines, and medical research papers.
Applications of Natural Language Processing in Clinical Research and Practice (N19-5)

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Challenge: a tutorial on clinical NLP will introduce students and experts to the field . a focus will be on the use of clinical Nlp in clinical research and practice .
Approach: This tutorial introduces the clinical use of natural language processing (NLP) techniques . it will review techniques and tools developed for the clinical domain .
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ELISA-EDL: A Cross-lingual Entity Extraction, Linking and Localization System (N18-5)

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Challenge: ELISA-EDL is a cross-lingual entity extraction, linking and localization system for Wikipedia languages.
Approach: They propose a cross-lingual entity extraction, linking and localization system for English speakers . it extracts entities from unstructured text in any of 282 Wikipedia languages and links them to English knowledge bases .
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CliniBench: A Clinical Outcome Prediction Benchmark for Generative and Encoder-Based Language Models (2026.eacl-long)

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Challenge: generative large language models are being investigated for complex medical tasks, but their effectiveness in real-world clinical applications remains underexplored.
Approach: They propose to compare encoder-based classifiers and generative LLMs for discharge diagnosis prediction from admission notes in a MIMIC-IV dataset.
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Named Entities in Medical Case Reports: Corpus and Experiments (2020.lrec-1)

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Challenge: Only very few annotated corpora in the medical domain exist.
Approach: They propose to annotate medical entities in case reports from PubMed Central's open access library.
Outcome: The proposed corpus is the first of its kind to be made available to the scientific community in English.

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