Clinical Translation and Validation Core

临床翻译和验证核心的目标是使用老年医学的科学和实践 老年学评估人工智能(AI)方法用于临床决策的可行性和临床实用性 支持和支持在家中监测老年人的新技术。认识到老年综合征 功能和认知障碍是健康结果和生活质量的最重要预测因素 目前识别和预防这些疾病的临床方法是反应性的， 这个核心的努力植根于这样一种信念，即人工智能和家庭监控拥有巨大的前景，可以颠覆 临床范式和革命性的检测、监测和护理老年人和那些有 AD/ADRD。核心领导层将利用他们在AD/ADRD、老年病学、老年学和人工智能方面的集体专业知识来 与PennAITech合作实验室的其他核心密切合作，以支持培训、利益相关者参与和 促进人工智能方法在决策支持和新技术领域的可行性和实用性的试点项目 回家。这个小组将共同完成以下目标：(1)成立一个专家小组，以评估 新的人工智能模型用于预测分析和临床决策的可行性和临床价值 支持和支持旨在监测老年人和AD/ADRD患者的新技术；(2)与 技术识别和培训核心以及网络和指导核心的构建和制定 提供新的人工智能软件和家庭监控技术的可搜索数据库，用于 与有兴趣合作、评估或采用此类工具的人建立联系的目的； (3)建立国家资源用于预测的人工智能模型的评估和部署 分析和临床决策支持；以及(4)与利益相关者参与核心合作伙伴建立 网站和设置网络，可用作监测老龄化成年人的新技术的试验台 以及患有AD/ADRD的人，重点是服务不足和农村人口。

The goal of the Clinical Translation and Validation Core is to use the science and practice of geriatrics and gerontology to assess the feasibility and clinical utility of artificial intelligence (AI) methods for clinical decision support and of new technology for monitoring aging adults in their home. Recognizing that geriatric syndromes and functional and cognitive impairment are the most important predictors of health outcomes and quality of life in older adults, and that current clinical approaches to identifying and preventing these conditions are reactive, this core's efforts are rooted in the belief that AI and home monitoring hold tremendous promise for disrupting the clinical paradigm and revolutionizing the detection, monitoring, and care of older adults and those with AD/ADRD. The core leadership will use their collective expertise in AD/ADRD, geriatrics, gerontology, and AI to work closely with the other PennAITech Collaboratory Cores to support training, stakeholder engagement, and pilot projects that promote the feasibility and utility of AI methods for decision support and new technology in the home. Together, this team will accomplish the following aims: (1) establish an expert panel to assess the feasibility and clinical value of new artificial intelligence models for predictive analytics and clinical decision support and of new technologies designed to monitor aging adults and those with AD/ADRD; (2) collaborate with the Technology Identification and Training Core and the Networking and Mentoring Core to build and make available a searchable database of new artificial intelligence software and home monitoring technology for the purpose of making connections with those interested in collaborating, evaluating, or adopting such tools; (3) establish a national resource for the evaluation and deployment of artificial intelligence models for predictive analytics and clinical decision support; and (4) partner with the Stakeholder Engagement Core to establish a network of sites and settings which can serve as a testbed for new technologies designed to monitor aging adults and those with AD/ADRD with an emphasis on underserved and rural populations.