Biomedical Entity Linking

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12 papers4 papers in the last four weeks, against 2 the four weeks before. 0.0% of all new papers.

Discrete Neural Interlingua for Ontology-Agnostic EHR Modeling
Oct 19, 2026Tong Ding, Caiwei Tian, Dongmin Bang +6Tokenization in Language Models EHR Foundation Models
Mass General Brigham AI Institute · Harvard University · Massachusetts Institute of Technology
SNO-PI: Label-Scarce SNOMED CT Entity Linking with Pre-trained Encoders and Curated Terminology Knowledge
Oct 19, 2026Piyawoot SongsiritatBiomedical Entity Linking Ontology-Guided Information Extraction
The University of Queensland, Greater Brisbane Clinical School, Brisbane, Australia
UMCR: Universal Medical Concept Recognition through Guideline Integration and Agentic Linking
Oct 12, 2026Fabrice Lamarche, Amal ZouaqBiomedical Entity Linking Clinical Information Extraction
LAMA-WeST Lab, Polytechnique Montréal, Mila – Quebec AI Institute
Training-Free BioNEL-RAG: Advancing Biomedical Entity Linking through Retrieval-Augmented Generation and Large Language Model
Oct 10, 2026Ziyi Chen, Hui Liu, Ziyang Ling +2Biomedical Entity Linking Entity Linking
School of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China · Department of Precision Machinery and Precision Instruments, University of Science and Technology of China, Hefei, China
BELXTR: Biomedical Entity Linking via Contextualized Token Retrieval
Sep 22, 2026Samuele Garda, Ulf LeserLate Interaction Retrieval Biomedical Entity Linking
Computer Science, Humboldt-Universität zu Berlin, Rudower Chaussee 25, 12489, Berlin, Germany
OntologyAligner: Ontology-Aligned Retrieval and Hierarchy-Guided Large Language Model Reranking for Biomedical Ontology Normalization
Sep 9, 2026Jie Song, Zhichuan Xu, Ziyu Lu +8Learning to Rank Biomedical Entity Linking
Department of Dermatovenereology and Institutes for Systems Genetics, Frontiers Science Center for Disease-related Molecular Network, West China Hospital, Sichuan University, Chengdu 610212, China · College of Health and Intelligent Engineering, Chengdu Medical College, Chengdu, Sichuan 610500, China
Neighborhood-Aware Dual Biomedical Entity Linking
Aug 4, 2026Yicheng Tao, Jie LiuLearning to Rank Biomedical Entity Linking
Department of Electrical Engineering and Computer Science, University of Michigan · Gilbert S. Omenn Department of Computational Medicine and Bioinformatics, University of Michigan
BeLink: Biomedical Entity Linking Meets Generative Re-Ranking
May 21, 2026Darya Shlyk, Stefano Montanelli, Lawrence HunterLLM Fine-Tuning Biomedical Entity Linking
University of Milan Milan, Italy · University of Chicago Chicago, IL, USA
What Do Biomedical NER and Entity Linking Benchmarks Measure? A Corpus-Centric Diagnostic Framework
May 19, 2026Robert Leaman, Rezarta Islamaj, Zhiyong LuNamed Entity Recognition Biomedical Entity Linking
National Library of Medicine, Bethesda, MD
LongBEL: Long-Context and Document-Consistent Biomedical Entity Linking
May 13, 2026Adam Remaki, Xavier Tannier, Christel GérardinBiomedical Entity Linking Long-Context Modeling
Sorbonne Université, Inserm, Université Sorbonne Paris Nord, Limics, 75006 Paris, France · Service de médecine interne, Hôpital Tenon, Assistance Publique - Hôpitaux de Paris, Paris, France
BioELX: Context-Aware Cross-lingual Biomedical Entity Linking without Task-Specific Supervision
Apr 9, 2026Yi Wang, Corina Dima, Liangyu Zhong +1LLM Reranking Multilingual IR
Institute for AI, University of Stuttgart · Technical University of Berlin · University of Southampton
Team Fusion@ SU@ BC8 SympTEMIST track: transformer-based approach for symptom recognition and linking
Apr 7, 2026Georgi Grazhdanski, Sylvia Vassileva, Ivan Koychev +1Named Entity Recognition Biomedical Entity Linking
FMI, Sofia University St. Kliment Ohridski · Ontotext

Oct 19, 2026J/K move · Enter open · S save

Discrete Neural Interlingua for Ontology-Agnostic EHR Modeling

Tong Ding, Caiwei Tian, Dongmin Bang, Ming Y. Lu+5

Mass General Brigham AI Institute · Harvard University · Massachusetts Institute of Technology

Tokenization in Language Models EHR Foundation Models Biomedical Entity Linking Vector Quantization

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EHR foundation models promise scalable clinical prediction across health systems, yet their deployment is constrained by a tokenization bottleneck. The same clinical concept can appear as different ontology codes, local identifiers, synonyms, or free-text descriptions, which standard EHR tokenizers treat as unrelated symbols. A model trained on MIMIC-III with a closed-vocabulary tokenizer can use only 13% of eICU events. We introduce MEDIATOR, a discrete ontology-agnostic tokenizer that maps any clinical concept expressed as text into a shared vector-quantized codebook, turning EHR harmonization into open-vocabulary tokenization without manual mappings or a fixed vocabulary. Trained with synonym supervision and guided by enriched concept descriptions, code co-occurrence, and relation graphs, MEDIATOR collapses equivalent expressions while organizing distinct concepts in a medically meaningful discrete space. Used as the token interface of an EHR Transformer, MEDIATOR improves mean AUPRC over the strongest prior tokenizer by 4.0 points (8% relative) on 20 MIMIC-III tasks and by 8.6 points (29% relative) in zero-shot transfer to 14 eICU tasks, where it uses all events. The transfer gain combines coverage and representation, as MEDIATOR remains the best tokenizer under identical inputs (+1.0 and +1.9 points on operational and subcohort-mortality tasks). Same-encoder controls show that the text encoder drives in-domain accuracy, while the learned objectives of MEDIATOR drive transfer robustness and entity-linking quality. MEDIATOR also enables transferable attribution across hospitals.