Clinical Translation and Validation Core

临床转化和验证核心

• 批准号: 10685541
• 负责人: JASON H KARLAWISH
• 金额: $ 14.9万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-30 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10685541
• 关键词: Address; Adopted; Adoption; Adult; Aging; Alzheimer' s Disease; Alzheimer' s Disease Core Center; Alzheimer' s disease related dementia; Area; Artificial Intelligence; Belief; Biological Markers; Board Certification; Caring; Civil Rights; Clinical; Collaborations; Communities; Computer software; Data; Databases; Decision Making; Detection; Development; Diagnostic; Elderly; Electronic Health Record; Engineering; Epidemiology; Ethics; Evaluation; Family; Feedback; Geriatrics; Gerontology; Goals; Grant; Health; Health Policy; Healthcare; Healthcare Systems; Home; Impaired cognition; Leadership; Medical Ethics; Medical Informatics; Medicine; Memory; Mentors; Modeling; Monitor; Neurology; Nursing Informatics; Outcome; Persons; Philadelphia; Pilot Projects; Predictive Analytics; Prevention; Quality of life; Research; Research Personnel; Resources; Role; Rural; Rural Population; Safety; Science; Site; Specialist; Syndrome; Technology; Training; Training Support; Underserved Population; Validation; Voting Right; Work; artificial intelligence method; biomedical informatics; clinical care; clinical decision support; clinical translation; collaboratory; dementia care; design; digital; experience; functional disability; healthy aging; improved; innovation; instrumental activity of daily living; interest; machine learning model; new technology; open source; patient home care; predict clinical outcome; predictive modeling; prevent; professor; searchable database; smart home; social stigma; socioeconomics; software development; synergism; tool; wearable device

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.

临床翻译和验证核心的目标是利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效用 支持和新技术，以监测老年人在他们的家里。认识到老年综合症 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 在老年人中，目前识别和预防这些疾病的临床方法是反应性的， 这一核心的努力植根于这样一种信念，即人工智能和家庭监控具有巨大的潜力， 临床范式和革命性的检测，监测，和老年人和那些有 AD/ADRD。核心领导层将利用他们在AD/ADRD、老年医学、老年学和人工智能方面的集体专业知识， 与其他PennAITech协作实验室核心密切合作，以支持培训、利益相关者参与，以及 试点项目，促进人工智能方法在决策支持和新技术中的可行性和实用性， 回家该小组将共同实现以下目标：（1）建立一个专家小组， 用于预测分析和临床决策的新人工智能模型的可行性和临床价值 支持和旨在监测老年人和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， 提供一个可搜索的数据库，其中包含新的人工智能软件和家庭监控技术， 与那些有兴趣合作，评估或采用这些工具的人建立联系的目的; (3)建立一个国家资源，用于评估和部署人工智能模型， 分析和临床决策支持;以及（4）与利益相关者参与核心合作， 一个网站和设置的网络，可以作为新技术的测试平台，旨在监测老年人 以及AD/ADRD患者，重点关注服务不足和农村人口。