HAL (France)
open access
Limited discriminative performance of endoscopic deep learning for Helicobacter pylori status assessment in gastric cancer patients: a retrospective 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
- Development of a Predictive Model for Gastric Cancer Peritoneal Metastasis and Cachexia Using BUB1 and Radiopathomics Data With Deep Learning#1138329
- Computational Prediction and Experimental Validation of Gastric Cancer Associated Neoantigens#125840
- Endoscopic Ultrasound-guided Needle-based Confocal Laser Endomicroscopy for Diagnosis of Gastric Subepithelial Tumors#852856
- Table 4_Machine learning–driven identification and experimental validation of key biomarkers in the bile acid metabolic pathway associated with ulcerative colitis.docx#480330
- Intelligent Support for Radiological Reporting of Lung Neoplasms#968902
Record · ID 482633
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