NCBI PubMed Central
open access
A time‑dependent risk prediction model for distant metastasis in early‑stage breast cancer based on explainable ensemble learning: a retrospective 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
- Clinically interpretable deep learning for breast cancer missense variant pathogenicity prediction.#430772
- St. Gallen International Breast Cancer Consensus-Based Clinical Decision Validation: Concordance Assessment Between Deep Large Language Model Outputs and Global Expert Panel Recommendations.#25838
- Prospective Validation of an AI Model for Predicting Liver Metastasis in Colorectal Cancer#857883
- Temporal Feature Engineering and Ensemble Learning for Predicting 28-Day Mortality in ICU Patients with Alcoholic Cirrhosis#417390
- Machine learning to develop and validate a model for predicting the risk of lymph node metastasis in colorectal cancer patients.#430807
Record · ID 452957
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