{
  "abstract": "Establishing the chief complaint requires identifying the patient’s main symptoms or concerns. This information is essential for triage and subsequent clinical assessment. However, patients may struggle to describe their symptoms or leave important concerns unspoken. Also, clinicians have limited time to ask further questions during intake. Generative AI could help by asking patients what is troubling them, when their symptoms began, and what other concerns they have. It could prepare a short summary for patients to correct and clinicians to review. Clinical studies of AI-assisted intake have reported shorter physician consultations and more complete recorded histories. These findings do not show whether AI helps clinicians establish the chief complaint more accurately. We propose an evaluation framework centered on the proportion of patients whose main symptoms or concerns are missing or incorrectly described after AI-assisted intake. Studies should compare what patients wanted to discuss with what the AI agent asked about and included in its summary. They should also examine whether concerns requiring urgent assessment were missed. The clinical goal is a clear description of the patient’s main symptoms and concerns that helps clinicians judge urgency and decide what needs attention.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA",
    "Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA",
    "BRIDGE GenAI Lab, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Vera Sorin"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Eyal Klang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/5y0kytv7hpy92.bib",
  "cited_by": 0,
  "doi": "10.3390/jcm15207912",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13706287/?tool=EBI",
  "id": "5y0kytv7hpy92",
  "issns": [
    "2077-0383"
  ],
  "landing_url": "https://www.mdpi.com/2077-0383/15/20/7912",
  "language": "eng",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "openalex",
      "2718|Artificial Intelligence in Healthcare and Education"
    ]
  ],
  "openalex": "W7221636237",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13706287/pdf/?tool=EBI",
  "pmcid": "PMC13706287",
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "MDPI AG",
  "ris": "https://research.draconitic.com/paper/5y0kytv7hpy92.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:20:00Z",
      "native_id": "10.3390/jcm15207912",
      "source": "crossref",
      "url": "https://www.mdpi.com/2077-0383/15/20/7912"
    },
    {
      "first_seen": "2026-10-30T12:21:25Z",
      "native_id": "PMC:PMC13706287",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13706287"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "Generative AI for Establishing the Chief Complaint",
  "title_text": "Generative AI for Establishing the Chief Complaint",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:21:25Z",
  "url": "https://research.draconitic.com/paper/5y0kytv7hpy92",
  "venue": "Journal of Clinical Medicine",
  "versions": []
}