Figshare
open access
In Copyright
Enhanced cardiovascular disease risk prediction using explainable machine learning and data balancing
cardiovascular-diseasedeep-learningexplainable-artificial-intelligencemachine-learningprecision-medicinerisk-prediction
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
- A Hybrid Predictive Ensemble of Machine Learning and Deep Neural Networks for Early Cardiovascular Disease Risk Assessment#660818
- A comparative performance analysis of ensemble learning and regularized neural networks in cardiovascular risk prediction.#476871
- Machine learning-based cardiovascular risk prediction in systemic lupus erythematosus: development and internal validation of a prognostic model#250288
- CardioAI: An Explainable Machine Learning System for Cardiovascular Risk Prediction and Patient Retention in Nigerian Healthcare Settings#147928
- CardioAI: An Explainable Machine Learning System for Cardiovascular Risk Prediction and Patient Retention in Nigerian Healthcare Settings#143860
Record · ID 438686
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