NCBI PubMed Central
open access
Prediction of Antimicrobial Resistance in People Living With Cystic Fibrosis Using Machine Learning.
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
- Forecasting Bacterial Antimicrobial Resistance Trends Using Machine Learning on WHO GLASS Surveillance Data: A Retrieval-Augmented Generation Approach for Policy Decision Support#1117331
- Antimicrobial Resistance in Cystic Fibrosis (CF)#363632
- A Study to Determine the Variability of a 6-Minute Walk Test in Cystic Fibrosis Subjects With Advanced Lung Disease#883052
- Identifying the Causes and Risk Factors of Pulmonary Exacerbations in Cystic Fibrosis#900467
- Prediction Methods for Antimicrobial Resistance Trends in China.#247603
Record · ID 452873
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