NCBI PubMed Central
open access
Quality and performance of machine learning versus logistic regression for predicting IVIG resistance in Kawasaki disease: a PROBAST+AI systematic comparison.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- The Zambia Ivermectin Trial for the Treatment and Prevention of COVID-19#1111481
- Next-Generation Sequencing for Pathogen Detection and Quantification in Children With Musculoskeletal Infections#1138571
- The Lancet Infectious Diseases Commission on Antimicrobial Resistance: 6 Years Later#323868
- Environmental conditions and animal hosts shape the spatial transmission risks of echinococcosis in China.#368495
- Safety and Efficacy of the MyokinE100 (CL-EMS Alpha) Device in Inducing Visible Muscle Contraction in Healthy Volunteers#858002
Record · ID 396274
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive