PubMed
open access
CC BY-NC 4.0
Development and validation of machine learning prognostic models for overall survival in non-surgical prostate cancer patients with bone metastases.
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
- Machine-Learning-Based Survival Prediction in Glioblastoma Using Graph-Theoretical Analysis of Structural Network Alterations#120134
- Machine-Learning-Based Survival Prediction in Glioblastoma Using Graph-Theoretical Analysis of Structural Network Alterations.#9293
- End-of-life prognostic models in advanced cancer: a scoping review of model development, validation, and impact#172141
- Prediction-model development and temporal validation for six-month cancer-specific mortality in de novo metastatic gastroesophageal junction adenocarcinoma: a SEER-based study.#666098
- Development of multi-algorithm machine learning models integrating novel serum biomarkers for survival prediction in colorectal cancer: a retrospective cohort study.#1147044
Record · ID 9669
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