Artificial Intelligence (AI) Summit

项目摘要 AI峰会的主要目标是： 与食品和药物管理局和业界的开放式协作和接触，讨论人工智能挑战和机遇 确定在整个医疗保健领域实施人工智能的创新解决方案。 AFDO建议AI峰会科学会议计划遵循以下格式： 2022年至2026年年将是一次面对面的会议，有演讲和促进的讨论 关于人工智能现在、过去和将来如何在医疗保健行业用于推进患者护理。 在每次会议期间，来自医疗行业各个领域的130名人工智能领导者将前来 共同展示在三个关键工作组之一完成的工作：AI in Operations Team(AIO)， 良好机器学习实践团队(GMLP)和关注点人工智能(AI@POC团队)。 AI in Operations Team是FDA和行业的一个有组织的跨行业讨论小组 致力于在所有运营中提高产品质量预测性保证的专业人员 通过人工智能的力量。这个团队试图解决的问题是缓解焦虑和 在扩大人工智能在作战中的使用方面犹豫不决。我们的目标是通力合作，实现 提高对人工智能使用的认识，并探索其他应用。 好的机器学习实践团队正在将人工智能活动的世界带入一个地方，以便 提高对当前良好工作的认识，同时也要通过协作进一步解决 解决与整个行业实施人工智能相关的挑战。这个团队试图解决的问题是 解决的办法是避免意外结果的风险，及时意外降级，混淆 用户，以及结果与可能使用进化算法输出的其他软件不兼容 来自机器学习。该组织的交付成果支持组织在 负责任和有效的方式。 AI at the Point of Care团队面向寻求以下目标的医生、医疗系统成员和创新者 利用人工智能来改善患者护理、临床工作流程、系统运营，并降低不必要的成本。 这个小组试图解决的问题是安全有效地开发和实现人工智能工具和 确定这样做所需的资源。该团队的重点是创建可交付成果，以提供 最大关系、结果和改进(ROI)。

Project Summary The key objectives of the AI Summit are:  Open collaboration and engagement with FDA and industry to discuss AI challenges and opportunities  Identify innovative solutions for implementing AI in across healthcare. AFDO proposes the AI Summit Scientific Meeting plan to follow this format:  Years 2022-2026 will be an in-person conference with presentations and facilitated discussions on how AI is, has been, and will be used in the healthcare industry to advance patient care. During each meeting, a group of 130+ AI leaders from all areas of the healthcare industry will come together to present work done in one of the three key working teams: AI in Operations Team (AIO), Good Machine Learning Practices Team (GMLP), and AI at the Point of Care (AI@POC Team). AI in Operations Team is an organized, cross-industry discussion group of FDA and industry professionals working to increase the predictive assurance of product quality across all operations through the power of AI. The problem this team is trying to solve is to alleviate the anxiety and hesitancy around expanding use of AI in operations. The goal is to work collaboratively towards increasing the awareness of AI use, and exploring additional applications. Good Machine Learning Practices Team is bringing the world of AI activity into one place in order to increase the awareness of the current good work, but also to collaboratively further solutions that address challenges related to AI implementation across the industry. The problem this team is trying to solve is to avoid the risks of unanticipated outcomes, unintended degradation in time, confusion for users, and incompatibility of results with other software that may use the output of evolving algorithms from machine learning. This group’s deliverables support the ability of organizations to use AI in a responsible and effective way. AI at the Point of Care Team is for physicians, healthcare systems members, and innovators seeking to leverage AI to improve patient care, clinical workflow, system operations, and reduce unnecessary costs. The problem this group is trying to solve is to safely and effectively develop and implement AI tools and identify the resources required to do so. This team’s emphasis is on creating deliverables that provide maximum Relationships, Outcomes, and Improvements (ROI).