bioRxiv / medRxiv
open access
CC BY-NC-ND 4.0
Consistent DNA methylation patterns enable accurate and interpretable cross-platform classification of central nervous system tumors
BackgroundDNA methylation-based classification has become an integral component of central nervous system (CNS) tumor diagnostics in neuro-oncology. However, current classifiers would benefit from improved interpretability, cross-platform generalizability, and scalability in routine clinical practic
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
- Performance analysis of automatic techniques for tissue classification in magnetic resonance images of the human brain#1020402
- Integrated multiclass driver ctDNA profiling enables MPNST detection and monitoring in NF1 patients#485078
- GPND-AI NULISA: A 15-Protein AI classifier for diagnosis and co-pathology profiling across neurodegenerative diseases.#145791
- Unimodal vs. multimodal deep learning for non-invasive MGMT promoter methylation prediction in glioblastoma: A systematic evaluation on the <i>BraTS</i> 2021 dataset#275941
- Glioblastoma MRI Dataset with Standardized Preprocessing, Expert-Validated Segmentation, and MGMT Profiling.#480897
Record · ID 1242663
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