{
  "abstract": "Background/Objectives: Myocardial perfusion scintigraphy (MPS) is a cornerstone non-invasive imaging modality for assessing myocardial ischemia and infarction. This pilot study aimed to evaluate the feasibility of using ChatGPT-4 for automated preliminary clinical reporting in MPS and to identify specific scenarios in which large language model (LLM) performance is robust versus inadequate. Methods: A comparative analysis was conducted using 30 consecutive de-identified MPS cases spanning a broad spectrum of clinical scenarios. Structured clinical data were input into ChatGPT-4 to generate AI-based preliminary reports, which were then compared with reports prepared by two experienced nuclear medicine physicians. Reports were independently evaluated using four criteria-clinical accuracy, report structure, terminological appropriateness, and overall comprehensibility-scored on a 5-point Likert scale. Inter-observer agreement was assessed using Cohen's kappa. Results: ChatGPT-4 demonstrated strong performance in report structure (median 5), terminological appropriateness (median 4), and overall comprehensibility (median 5), consistently producing well-organized and coherent reports. However, clinical accuracy was significantly lower compared with physician reports (median 4 vs. 5; p = 0.002; effect size r = 0.52), particularly in complex cases such as multivessel ischemia and mixed pathologies, where outputs were occasionally superficial or lacked specificity. Inter-observer agreement between evaluating physicians was substantial (Cohen's κ = 0.78; 95% CI: 0.64-0.92). Conclusions: ChatGPT-4 shows promise as a supportive tool for preliminary MPS reporting and medical education, but its limitations in higher-order clinical reasoning necessitate careful human oversight. These findings are preliminary and require validation in adequately powered, multicenter studies before any clinical implementation.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Nuclear Medicine, Mersin City Training and Research Hospital, 33240 Mersin, Turkey.",
    "Department of Family Medicine, Mersin City Training and Research Hospital, 33240 Mersin, Turkey."
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Mutlay Keskin",
      "orcid": "0000-0003-2528-8648"
    },
    {
      "affs": [
        1
      ],
      "name": "Ece Oğuz"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/3apqsspwpam62.bib",
  "cited_by": 0,
  "doi": "10.3390/diagnostics16193110",
  "fulltext_url": "https://europepmc.org/articles/PMC13664008",
  "id": "3apqsspwpam62",
  "issns": [
    "2075-4418"
  ],
  "landing_url": "https://europepmc.org/article/MED/42882264",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "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": "W7214194526",
  "pdf_url": "https://europepmc.org/articles/PMC13664008?pdf=render",
  "pmcid": "PMC13664008",
  "pmid": "42882264",
  "published": "2026-09-24",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/3apqsspwpam62.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:16Z",
      "native_id": "MED:42882264",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42882264"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2718|Artificial Intelligence in Healthcare and Education",
      "subfield": "epidemiology-public-health"
    }
  ],
  "title": "ChatGPT-4-Based Automated Preliminary Clinical Reporting in Myocardial Perfusion Imaging: A Pilot Evaluation.",
  "title_text": "ChatGPT-4-Based Automated Preliminary Clinical Reporting in Myocardial Perfusion Imaging: A Pilot Evaluation.",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:16Z",
  "url": "https://research.draconitic.com/paper/3apqsspwpam62",
  "venue": "Diagnostics (Basel, Switzerland)",
  "versions": []
}