NCBI PubMed Central
open access
Machine Learning Application to Predict Bicycle Ergometer Test Results: a Prospective Cohort Study.
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
- Development and validation of a machine learning-based model for assessing coronary artery disease risk in postmenopausal women: a dual-center retrospective study.#236058
- Predictors of Undiagnosed Diabetes in the Bangladeshi Female Population: A Propensity Score-Weighted Machine Learning Analysis of BDHS Biomarker Data.#305095
- Examining the Effects of a Remotely-delivered, Racially-tailored Exercise Training Program for Immediate and Sustained Improvements in Walking Dysfunction, Symptoms, and Health-related Quality of Life (HRQOL) Among African-Americans With Multiple Sclerosis (MS) Residing in Rural Environments.#1074539
- Improving sport horse selection using machine learning: Early prediction of elite-level show jumping performance.#975821
- Predicting major adverse cardiovascular and cerebrovascular events in chronic heart failure: a machine learning study.#276008
Record · ID 199184
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