arXiv (All)
open access
Solve the Missing First Step: Can VLMs Standardize Raw Heterogeneous Medical Data?
As vision-language models (VLMs) are increasingly applied to medical AI, existing benchmarks mainly focus on evaluating their diagnostic ability over given medical images and texts, implicitly assuming that standardized medical images, texts, or question-answer pairs are already prepared. However, t
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
- Calibrated Confidence Expression for Radiology Report Generation#1052115
- Assess the Clinical and Public Health Impact of The Combined Work of Physicians and AI Systems#83774
- Performance of an OCR-Prompt-LLM Integrated Workflow for Extracting Multi-dimensional Clinical Data in Ischemic Heart Disease#837298
- SynerMedGen: Synergizing Medical Multimodal Understanding with Generation via Task Alignment#1109055
- MedFoundationHub: A Lightweight and Secure Toolkit for Deploying Medical Vision Language Foundation Models.#1039866
Record · ID 999822
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