Application of artificial intelligence models in the identification of severe scrub typhus
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
Record details
Published: 22 July 2026
Source: Frontiers in Artificial Intelligence
Category: Research
Topics: Healthcare
Retrieved: 23 July 2026
Related evidence
These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.
On the fragility of neural architecture search: the role of overfitting and task complexity in medical image analysis
Frontiers in Artificial Intelligence · 22 July 2026
Correction: Performance of large language models in neonatal resuscitation assessments versus healthcare providers: an exploratory study
Frontiers in Artificial Intelligence · 22 July 2026
Large language models and multimodal AI for mental health: a systematic review of early diagnosis and monitoring
Artificial Intelligence Review · 22 July 2026
Associations Between Support-Seekers' Cross-Community Interactions and Their Engagement with Received Comments in Online Health Communities
arXiv cs.HC · 22 July 2026
Deep Shape Regression for Planar Curves with Multimodal Covariates
arXiv cs.LG · 21 July 2026
Communication Barriers in Patient-Provider Interactions in Health Care: Scoping Review
JMIR (Journal of Medical Internet Research) · 21 July 2026
How to cite this record
ethics.ai (22 July 2026), “Application of artificial intelligence models in the identification of severe scrub typhus,” evidence record 12739, https://ethics.ai/record/12739 (originally published by Frontiers in Artificial Intelligence).
Use and limitations
This page is a stable index and citation surface for a source record. ethics.ai did not author the underlying report and has not independently verified every claim. Automatic topics may be imperfect. For consequential use, quote and cite the original publisher.