{
  "id": 12739,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1842584",
  "title": "Application of artificial intelligence models in the identification of severe scrub typhus",
  "summary": "This retrospective study enrolled 492 patients with scrub typhus in Jiangmen from 2013 to 2025. Clinical and laboratory data were analyzed using univariate logistic regression and LASSO regression to identify risk factors for severe illness. Seven machine-learning models, including logistic regression, support vector machine, random forest, XGBoost, Naive Bayes, k-nearest neighbor, and decision tree, were constructed and externally validated. Variable importance was ranked using SHAP analysis. M",
  "authors": "Chunyu Chen",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-22T00:00:00.000Z",
  "fetched_at": "2026-07-23T05:10:49.458Z",
  "source_slug": "x-frontiers-in-artificial-intelligence",
  "source_name": "Frontiers in Artificial Intelligence",
  "source_homepage": "https://www.frontiersin.org/journals/artificial-intelligence",
  "ethics_ai_record_url": "https://ethics.ai/record/12739",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1842584",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}