@inproceedings{karakkaparambil-james-etal-2026-semantic,
    title = "Semantic Echo Pathways ({SEP}): Tracing How Medical Language Propagates and Transforms",
    author = "Karakkaparambil James, Charu  and
      Monteiro, Marcio  and
      Fellenz, Sophie",
    editor = {Danilova, Vera  and
      Kurfal{\i}, Murathan  and
      S{\"o}derfeldt, Ylva  and
      Reed, Julia  and
      Burchell, Andrew},
    booktitle = "Proceedings of the 1st Workshop on Linguistic Analysis for Health ({H}ea{L}ing 2026)",
    month = mar,
    year = "2026",
    address = "Rabat, Morocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.healing-1.5/",
    pages = "55--66",
    ISBN = "979-8-89176-367-8",
    abstract = "We introduce Semantic Echo Pathways (SEP), a new approach for modeling the cross-domain evolution of medical language. Using continual neural topic models (CoNTM) trained separately on scientific literature, clinical notes, and public health-related data, we track linguistic drift and identify points where concepts change meaning. We propose three novel metrics: Cross-Domain Drift Score, Temporal Echo Lag, and Semantic Mutation Patterns to quantify how medical language travels between the scientific, clinical, and public domain. Applications to evolving concepts such as ``long COVID'', diagnostic category changes reveal previously undocumented patterns of medical-semantic evolution. Our results bridge computational modeling with the human-centered perspectives of medical humanities, offering clear, domain-aware maps of how medical language shifts across time and domains, and combining quantitative analysis with linguistic and clinical insight."
}