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通过自适应系统的动态部署对医学人工智能的临床试验进行重新思考。

Rethinking clinical trials for medical AI with dynamic deployments of adaptive systems.

作者信息

Rosenthal Jacob T, Beecy Ashley, Sabuncu Mert R

机构信息

Tri-Institutional MD-PhD program of Weill Cornell/Rockefeller/Sloan Kettering, New York, NY, USA.

Department of Radiology, Weill Cornell Medicine, New York, NY, USA.

出版信息

NPJ Digit Med. 2025 May 6;8(1):252. doi: 10.1038/s41746-025-01674-3.

Abstract

There is a growing recognition of the need for clinical trials to safely and effectively deploy artificial intelligence (AI) in clinical settings. We introduce dynamic deployment as a framework for AI clinical trials tailored for the dynamic nature of large language models, making possible complex medical AI systems which continuously learn and adapt in situ from new data and interactions with users while enabling continuous real-time monitoring and clinical validation.

摘要

人们越来越认识到在临床环境中安全有效地部署人工智能(AI)进行临床试验的必要性。我们引入动态部署作为一种针对大语言模型的动态特性量身定制的AI临床试验框架,使复杂的医学AI系统成为可能,这些系统能够在原地从新数据以及与用户的交互中持续学习和适应,同时实现持续的实时监测和临床验证。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64e2/12056174/0ec3c050bb0a/41746_2025_1674_Fig1_HTML.jpg

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