arXiv cs.AI· Jing Yang, Long R. Jiao, Zongjiu Zhang, Xiujun Cai·· 12 小时前AI 评分34
临床判断成为预测捷径：临床 AI 部署前必须回答的两个问题
When Clinical Judgment Becomes a Predictive Shortcut: Two Questions Clinical AI Must Answer Before Deployment
AI 导读
临床 AI 能利用现有临床判断产生的信息来预测结果，但仅凭这种表现无法证明其在识别前或跨护理流程中的实用性。研究提出按预期用途和信息条件匹配的证据要求，并增加状态参照与代理相对时序测试，以支撑更强的识别声明。该框架指出，当前评估实践中的泄漏检查、整体预测性能和外部验证均未覆盖这些问题。
正文 · 原文
Abstract:Clinical AI can predict outcomes using information generated by existing clinical judgment. Such performance alone cannot establish usefulness before recognition or across care processes. We propose evidence requirements matched to intended use and information conditions, with additional state-reference and proxy-relative timing tests for stronger recognition claims. This framework helps hospitals assess whether the conditions supporting performance hold when assistance is most needed. These questions remain outside current evaluation practice leakage checks, overall predictive performance, and external validation do not address them; the framework makes them explicit and specifies the direct evidence required to answer them.
| Comments: | 27 pages, 1 figure, 3 tables, 1 box; includes Multimedia Appendix 1 |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2609.25852 [cs.AI] |
| (or arXiv:2609.25852v2 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2609.25852 arXiv-issued DOI via DataCite |
Submission history
From: Jing Yang [view email]
[v1]
Tue, 22 Sep 2026 08:16:44 UTC (1,636 KB)
[v2]
Fri, 23 Oct 2026 17:33:10 UTC (1,522 KB)
来源：arXiv cs.AI · arxiv.org