@inproceedings{nguyen-etal-2026-fhexchange,
    title = "{FH}exchange: Resources for Family Health History Extraction and Normalization From Consumer Dialog Sources",
    author = "Nguyen, Michelle  and
      Soley, Nidhi  and
      Zirikly, Ayah  and
      Sedoc, Jo{\~a}o  and
      Taylor, Casey",
    editor = "Demner-Fushman, Dina  and
      Ananiadou, Sophia  and
      Roberts, Kirk  and
      Tsujii, Junichi",
    booktitle = "{B}io{NLP} 2026",
    month = jul,
    year = "2026",
    address = "San Diego, California",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.bionlp-1.82/",
    pages = "1014--1028",
    ISBN = "979-8-89176-434-7",
    abstract = "Family health history (FHx) offers insight into a person{'}s health and disease risk, but it is largely held within free-text clinical formats that require processing for maximal utility of the data. The rapid deployment of ambient AI scribes and conversational agents in clinical settings necessitates evaluation on dynamic patient-clinician and patient-agent dialogs. To address this gap, we introduce two new datasets of patient FHx dialog documents designed to benchmark information extraction and entity linking. Distinct from clinician-entered datasets, patient-reported dialog data has its own semantic and content characteristics, which need to be studied for more patient-centered healthcare. We contribute a publicly available resource called FHexchange, with new annotations for family members, clinical observations, related entities, and standardized UMLS CUIs, offering the clinical NLP community a robust evaluation bed for emerging generative AI tools."
}