mlsanityData to 14 Oct 2026

From Regulatory Approvals to Patents: Cross-Domain Linking for Cardiovascular Device Traceability

arXiv 2606.28353 ↗First posted 6 Jun 2026cs.IR cs.AIcited by 0

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Abstract (arXiv)

Linking FDA-approved medical devices to their underlying United States Patent and Trademark Office (USPTO) patents enables critical applications such as recall root-cause analysis, M&A-driven IP discovery, and technology trajectory mapping. However, this cross-domain entity linking task remains unexplored due to severe *semantic gaps*: FDA documents focus on clinical outcomes, while patents describe technical mechanisms, yielding minimal lexical overlap. We formalize medical device-patent linking as a challenging cross-domain entity linking problem characterized by label scarcity and domain shifts. Using cardiovascular devices as a high-impact, representative domain featuring diverse technologies, high recall rates, and abundant disclosures, we construct a benchmark with 434 devices, 698K patents, and 585 high-fidelity expert-verified pairs. To address these challenges, we propose Bridge-MedDevKG, a coarse-to-fine framework that integrates (1) **MedDevOnto**, a domain-specific ontology that anchors device concepts via three-tier UMLS normalization; (2) **Multi-signal candidate generation** fusing company affiliation, semantic similarity, and ontology-weighted entity overlap; and (3) **Heterogeneous reranking** with multi-signal scoring and XGBoost classification on hard negatives. Our approach achieves a conservative lower-bound recall of 91.6% on the gold standard with 50.9% noise reduction, substantially outperforming LLM baselines under comparable evaluation. The resulting MedDevKG provides 6.8M high-confidence links, laying a scalable foundation for regulatory-IP integration across medical specialties.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 12 of its 30 references that are in the map. First posted on arXiv 6 Jun 2026.

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References · 12

  1. 2019Sentence-BERT: Sentence Embeddings using Siamese BERT-Networkscited by 9,170
  2. 2020Dense Passage Retrieval for Open-Domain Question Answeringcited by 3,824
  3. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,947
  4. 2019Passage Re-ranking with BERTcited by 645
  5. 2021Improving Biomedical Pretrained Language Models with Knowledgecited by 36
  6. 2021Engineering Knowledge Graph from Patent Databasecited by 18
  7. 2024LLM-RankFusion: Mitigating Intrinsic Inconsistency in LLM-based Rankingcited by 16
  8. 2018Zero-shot Neural Transfer for Cross-lingual Entity Linkingcited by 11
  9. 2024PubMed knowledge graph 2.0: Connecting papers, patents, and clinical trials in biomedical sciencecited by 8
  10. 2021Improving Zero-Shot Entity Retrieval through Effective Dense Representationscited by 6
  11. 2022Disentangled Modeling of Domain and Relevance for Adaptable Dense Retrievalcited by 4
  12. 2022Structure and Semantics Preserving Document Representationscited by 2

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