{
  "abstract": "Unless Kawasaki disease (KD) is promptly treated with intravenous immunoglobulin (IVIG), patients may develop IVIG-unresponsiveness and aneurysm. We analysed 628 KD and 155 KD-like cases to develop machine learning models for having KD (i.e., being diagnosed with KD), IVIG-unresponsiveness and aneurysm formation. We applied LASSO logistic regression to illness-day-indexed data incorporating family/previous histories and laboratory variables (e.g., neutrophils, total bilirubin, C-reactive protein, and AST). Optional inputs included BNP, IgG, fibrinogen, and echocardiographic Z scores. On Day 4, all models achieved AUCs > 0.7 in the test dataset: having KD (0.779), IVIG-unresponsiveness (0.772), and aneurysm formation (0.710). On Day 5, the model achieved a positive predictive value > 90% for having KD. When combined with predictions of unresponsiveness or aneurysm, 90% of complicated KD cases were identified. These models were implemented in a web-based and intranet-integrated application, enabling early diagnosis and risk stratification of KD across resource-limited and resource-rich settings.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": null,
  "author_total": 8,
  "authors": [
    {
      "name": "Yoshiro Nagao",
      "orcid": "0000-0003-3411-0729"
    },
    {
      "name": "Nobuhisa Kita"
    },
    {
      "name": "Shunsuke Fujii"
    },
    {
      "name": "Sumito Sameshima"
    },
    {
      "name": "Yoshimi Nishimura"
    },
    {
      "name": "Hiroe Okubo"
    },
    {
      "name": "Hisashi Endo"
    },
    {
      "name": "Ichiro Yamane"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c9b6zv9n0j5jq.bib",
  "cited_by": 0,
  "doi": "10.1038/s41598-026-77440-6",
  "fulltext_url": null,
  "id": "c9b6zv9n0j5jq",
  "issns": [
    "2045-2322"
  ],
  "landing_url": "https://www.nature.com/articles/s41598-026-77440-6",
  "language": null,
  "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",
      "2746|Kawasaki Disease and Coronary Complications"
    ]
  ],
  "openalex": "W7223439761",
  "pdf_url": "https://www.nature.com/articles/s41598-026-77440-6_reference.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-24",
  "publisher": "Springer Science and Business Media LLC",
  "ris": "https://research.draconitic.com/paper/c9b6zv9n0j5jq.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:33Z",
      "native_id": "10.1038/s41598-026-77440-6",
      "source": "crossref",
      "url": "https://www.nature.com/articles/s41598-026-77440-6"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2746|Kawasaki Disease and Coronary Complications",
      "subfield": "surgery"
    }
  ],
  "title": "A machine learning-based web application aids Kawasaki disease diagnosis and predicts its outcomes",
  "title_text": "A machine learning-based web application aids Kawasaki disease diagnosis and predicts its outcomes",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:17:33Z",
  "url": "https://research.draconitic.com/paper/c9b6zv9n0j5jq",
  "venue": "Scientific Reports",
  "versions": []
}