arXiv (All)
open access
Towards AI-Assisted Clinical Trial Matching: Practical Considerations, Multicenter Evaluation, and Real-World Deployment
Clinical trials are essential for advancing cancer care and drug development, but many fail because of insufficient patient enrollment. While there is growing interest in using AI to support patient recruitment, existing systems largely perform eligibility assessment alone and have rarely been evalu
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
- ACTIVATE: AI-driven Clinical-trial Trial-Information and Viability Assessment Tool for EHRs#1094267
- CTO: A Community-Based Clinical Trial Ontology and Its Applications in PubChemRDF and SCAIViewH#748609
- Development and Feasibility Evaluation of an Edge AI as Medical Device System for Breast Cancer Multidisciplinary Team Meetings#1109130
- Integrated Patient Avatars for Guiding Systemic Therapy Treatments in Metastatic Breast Cancer Patients#1173519
- Data Management and Sharing Plan for: Supervised Weighted Distances: Patient Similarity to Explain Clinical AI Models#649107
Record · ID 821166
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