Biomedical IR

IR: Information Retrieval

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Overview

Biomedical information retrieval finds evidence in resources such as PubMed, electronic health records, and biomedical knowledge graphs to support literature review, clinical question answering, trial matching, and terminology coding. Systems combine sparse search such as BM25 with dense biomedical encoders, hybrid rank fusion, query expansion, cross-encoder reranking, and structured knowledge from ontologies or constraints. Benchmarks including BioASQ, PubMedQA, TREC-COVID, and clinical-record QA tests measure relevance and downstream answer quality, but gains in retrieval do not always translate into more accurate answers. Key challenges include synthesizing evidence across documents and encounters, handling conflicting or temporally qualified claims, and maintaining performance across languages and complex relational queries.

Latest papers

CardsList

43 papers7 papers in the last four weeks, up 17% on the four weeks before. 0.0% of all new papers.

  1. Self-Driving Datasets: From 20 Million Papers to Nuanced Biomedical Knowledge at Scale

    May 7, 2026Haydn Jones, Yimeng Zeng, Alden Rose +11AI Agents for Scientific DiscoveryLLM Information Extraction

    Department of Computer and Information Science, University of Pennsylvania · Department of Genetics, University of Pennsylvania · 3Departments of Bioengineering and Chemical and Biomolecular Engineering,2026 University of Pennsylvania

  2. GATHER: Convergence-Centric Hyper-Entity Retrieval for Zero-Shot Cell-Type Annotation

    May 7, 2026Zhonghui Zhang, Feng Jiang, Shaowei Qin +2Zero-Shot LearningGraph Retrieval-Augmented Generation

    Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology Shenzhen, China · Software College, Northeastern University Shenyang, China

  3. Benchmarking Retrieval Strategies for Biomedical Retrieval-Augmented Generation: A Controlled Empirical Study

    May 4, 2026Devi Prasad Bal, Subhashree PuhanCross-Encoder RerankingRetrieval-Augmented Generation

    The University of Texas at Austin

  4. Diagnosable ColBERT: Debugging Late-Interaction Retrieval Models Using a Learned Latent Space as Reference

    Apr 21, 2026François RemyInterpretable MLMulti-Vector Retrieval

    Parallia AI

  5. BioHiCL: Hierarchical Multi-Label Contrastive Learning for Biomedical Retrieval with MeSH Labels

    Apr 17, 2026Mengfei Lan, Lecheng Zheng, Halil KilicogluContrastive LearningHierarchical Representation Learning

    University of Illinois Urbana-Champaign

  6. Hybrid Retrieval for COVID-19 Literature: Comparing Rank Fusion and Projection Fusion with Diversity Reranking

    Apr 15, 2026Harishkumar Kishorkumar PrajapatiHybrid RetrievalBiomedical IR

    School of Electronic Engineering and Computer Science Queen Mary University of London, London, UK

  7. SatIR: Scalable High-Recall Constraint-Satisfaction-Based Information Retrieval for Clinical Trials Matching

    Apr 10, 2026Zikai Zhou, Yufei Jin, Yilin Xu +3HealthcareSatisfiability Modulo Theories

    Department of Computer Science, Stanford University, Stanford, CA, USA · Samueli Electrical and Computer Engineering, UCLA, Los Angeles, CA, USA · Department of Computer Science, Emory University, Atlanta, GA, USA +1

  8. PubMed Reasoner: Dynamic Reasoning-based Retrieval for Evidence-Grounded Biomedical Question Answering

    Mar 28, 2026Yiqing Zhang, Xiaozhong Liu, Fabricio MuraiBiomedical QAAgentic RAG

    PayPal · Worcester Polytechnic Institute

  9. Graph-Aware Late Chunking for Retrieval-Augmented Generation in Biomedical Literature

    Mar 23, 2026Pouria Mortezaagha, Arya RahgozarRetrieval-Augmented GenerationBiomedical IR

    Methodological Implementation Research, Ottawa Hospital Research Institute, Ottawa, ON, Canada · School of Engineering Design and Teaching Innovation, University of Ottawa, Ottawa, ON, Canada

  10. Errors in AI-Assisted Retrieval of Medical Literature: A Comparative Study

    Mar 21, 2026Jenny Gao, Yongfeng Zhang, Mary L Disis +1LLM ReliabilityBiomedical IR

    College of Arts and Science, New York University, New York, NY · College of Arts and Science, New York University, New York, NY 10003 · Department of Computer Sciences, School of Arts & Sciences, Rutgers University, Piscataway, NJ +9

  11. ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics

    Mar 12, 2026Omar CoserAI Agents for Scientific DiscoverySingle-Cell Transcriptomics

  12. PathoScribe: Transforming Pathology Data into a Living Library with a Unified LLM-Driven Framework for Semantic Retrieval and Clinical Integration

    Mar 9, 2026Abdul Rehman Akbar, Samuel Wales-McGrath, Alejadro Levya +5Biomedical IRComputational Pathology

    Department of Pathology, College of Medicine, The Ohio State University Wexner Medical Center, Columbus, OH, USA · Department of Pathology and Laboratory Medicine, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA · PathPresenter

  13. Modular Expert Merging for Biomedical Retrieval

    Feb 4, 2026Sameh Khattab, Jean-Philippe Corbeil, Osman Alperen Çinar-Koraş +5Model MergingDense Retrieval

    Institute for Artificial Intelligence in Medicine (IKIM), University Hospital Essen, Germany · Faculty of Computer Science, University of Duisburg-Essen, Germany · Microsoft Healthcare & Life Sciences, Canada +1