arXiv (All)
open access
Current validation practice undermines surgical AI development
Surgical data science (SDS) is rapidly advancing, yet clinical adoption of artificial intelligence (AI) in surgery remains limited, with inadequate validation as an important contributing factor. Existing validation practices often neglect the temporal and hierarchical structure of intraoperative vi
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
- [Artificial intelligence in surgical disciplines: Clinical application, advantages, and potential-a Delphi expert consensus].#263193
- Artificial intelligence in the surgical management for colorectal cancer: current applications and future directions.#1299776
- Machine learning and artificial intelligence for clinical prediction in orthopaedic surgery: a bibliometric analysis of 1,739 publications, 2015–2026#447724
- Revolutionizing Healthcare with Artificial Intelligence -A Machine Learning- Driven Approach to Precision Medicine, Predictive Analytics, and Automated Clinical Decision Support#717766
- Precision Medicine and Artificial Intelligence in Next-Generation Cancer Surgery: A Comprehensive Analysis of Clinical Applications, Therapeutic Outcomes, and Implementation Strategies.#263196
Record · ID 1354823
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