ClinicalTrials.gov
public full text
Public Domain
Histopathology Images Based Survival Prediction of Glioma Patients Using Artificial Intelligence
This registry aims to collect clinical, molecular and histopathology imaging including detailed survival data, clinical parameters, molecular pathology (1p/19q codeletion, MGMT methylation, IDH and TERTp mutations, etc) and images of HE slices in primary gliomas. By leveraging artificial intelligence, this registry will seek to construct and refine hstopathology imaging based algorithms that able to predict patients' survivals in the frame of molecular pathology or subgroups of gliomas.
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 of an Artificial Intelligence Model for Optimising Therapy in Gliomas Gliomas#1229620
- Data Management and Sharing Plan for: Targeting Amino Acid Metabolism in Glioblastoma#263845
- Survival Significance of Molecular Pathology and Genetic Variation in Brain Gliomas#1369980
- Post-Neoadjuvant Treatment MRI Based AI System to Predict pCR for Rectal Cancer#1114871
- AI-Based Methods in Neuropathology for Diagnosis and Treatment of Brain Tumors.#121121
Record · ID 1466268
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