ClinicalTrials.gov
public full text
Public Domain
Development of Multiphasic CT-based Delta-Radiomics Model for Predicting Postoperative Recurrence Risk in Bladder Cancer
This retrospective study included 316 bladder cancer patients
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
- Application of Radiomics-based AI Models in Predicting Clinical Outcome of Patients With Renal Cell Carcinoma After Surgical Treatment#897480
- Development and Validation of a Clinical Radiomics Nomogram for Predicting Early Recurrence After Microwave Ablation in Hepatocellular Carcinoma Patients With Type 2 Diabetes.#392770
- Multi-regional radiomics based on planning CT and information complementarity between GTVp and GTVn: an explainable model for predicting 5-year recurrence risk in HPV-positive oropharyngeal cancer.#1175524
- Pretreatment 18F-FDG PET/CT Radiomics for Predicting Response to First-Line Targeted Therapy Plus Immunotherapy in Metastatic Renal Cell Carcinoma#1046204
- Longer-term Recurrence Rates in Patients With Bladder Cancer After Hexvix (Cysview)Fluorescence Cystoscopy/TURB#903049
Record · ID 883975
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