As artificial intelligence rapidly advances in healthcare, the industry is grappling with how to evaluate AI models for accuracy and performance and monitor the technology for any downstream adverse outcomes.EHR giant Epic plans to release an AI validation software suite to enable healthcare organizations to evaluate AI models at the local level and monitor those systems over time, Seth Hain, Epic senior vice president of R&D, said in an exclusive interview.Epic has developed an AI software suite, what the company calls an 'AI trust and assurance software suite,' that automates data collection and mapping to provide near real-time metrics and analysis on AI models.

随着人工智能在医疗保健领域的迅速发展，该行业正在努力评估人工智能模型的准确性和性能，并监测技术的任何下游不良后果。Epic研发高级副总裁塞思·海恩（SethHain）在一次独家采访中表示，EHR巨头Epic计划发布一套人工智能验证软件，使医疗保健组织能够在当地评估人工智能模型，并随着时间的推移监控这些系统。Epic开发了一个人工智能软件套件，该公司称之为“人工智能信任和保证软件套件”，该套件自动化数据收集和映射，以提供人工智能模型的近实时度量和分析。

The automation creates consistency and eliminates the need for healthcare organization data scientists to do their own data mapping—the most time-consuming aspect of validation, according to Hain.The key is to enable AI testing and validation at a local level and allow ongoing monitoring at scale, Hain noted.'We'll provide health systems with the ability to combine their local information about the outcomes around their workflows, alongside the information about the AI models that they're using, and they will be able to use that both for evaluation and then importantly, ongoing monitoring of those models in their local contexts,' Hain said during the interview.The company is putting its hefty weight behind the idea that AI validation standards should be tested on local patient populations and include ongoing monitoring.A critical access hospital in rural Nebraska sees a different mix of patients and has different workflows than a dedicated cancer center in New York City, experts point out.

根据Hain的说法，自动化产生了一致性，消除了医疗保健组织数据科学家自己绘制数据映射的需要，这是验证中最耗时的方面。Hain指出，关键是在地方层面实现人工智能测试和验证，并允许大规模持续监测海恩在采访中说：“我们将为卫生系统提供能力，使其能够结合当地有关其工作流程结果的信息，以及他们正在使用的人工智能模型的信息，并且他们将能够使用这些信息进行评估，然后重要的是，在当地情况下对这些模型进行持续监测。”。该公司正在大力支持人工智能验证标准应在当地患者人群中进行测试并包括持续监测的想法。专家指出，内布拉斯加州农村的一家重症医院与纽约市专门的癌症中心相比，患者的组合和工作流程有所不同。

And a critical access hospital in one rural part of the country will have a different patient population than a hospital .

在该国的一个农村地区，重症监护医院的患者人数将与医院不同。