Building BRIDGEs: Coordinating Standards, Diversity, and Ethics to Advance Biomedical AI

搭建桥梁：协调标准、多样性和道德以推进生物医学人工智能

• 批准号: 10801686
• 负责人: ALEX BUI
• 金额: $ 58.6万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-07-06 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10801686
• 关键词: Adoption; Anxiety; Appointment; Automobile Driving; Award; Bridge to Artificial Intelligence; Clinical; Communities; Complement component C1; Consultations; Data Science; E-learning; Education; Educational Curriculum; Equity; Ethics; Faculty; Fostering; Future; Goals; Growth; Healthcare; Hour; Leadership; Medical; Medical Informatics; Medical Students; Medicine; Mentors; Mentorship; Mission; Modernization; Nurses; Physicians; Process; Protocols documentation; Reporting; Research Personnel; Societies; Specialist; Strategic Planning; Technology; Training; Trust; Underrepresented Minority; United States National Institutes of Health; Vision; career; clinical care; clinical practice; cohort; community building; design; diverse data; driving force; empowerment; experience; innovation; medical schools; minority communities; multidisciplinary; next generation; programs; recruit; skills; trustworthiness

The NIH's Strategic Plan for Data Science sets forth a grand and ambitious goal to enhance the diversity of the data science workforce and to engage underrepresented minority communities. Indeed, the vision of an ethical and equitable society supported by modern AI/ML healthcare innovations can only be achieved when our stake- holders include representatives of all communities. In lockstep with the NIH's diversity goals, this application aims to enact long-lasting change in the biomedical AI/ML community by a key leadership workforce to advance our mission in fostering the growth of a diverse next-generation multidisciplinary cohort of physicians and inves- tigators who are the driving force enabling Bridge2AI. Briefly, we recognize a major challenge in biomedical AI/ML education that limits the widespread adoption of modern AI/ML in health care and biomedical innovations. There exists a general lack of understanding regarding ethical and trustworthy AI (ETAI) in our workforce, com- bined with public anxiety surrounding the use of AI/ML applications. These concerns stifle the potential impact of these AI/ML technologies. Accordingly, we propose to establish the Bridge2AI-ENABLE Scholar Award. Essential to the successful implementation of AI/ML strategies are the emerging underrepresented in medicine (URiM); these professionals (e.g., medical students, clinical fellows, nurses, physicians) are well-trained in their medical professions and are committed to undergo further training in AI/ML and to advance clinical practice. Our proposed Bridge2AI-ENABLE Scholar Award will offer targeted AI/ML training for up to 15 URiM medical profes- sionals who are poised to become future leaders driving AI/ML innovation in health care. This URiM enrichment activity will consist of designated mentor teams composed of clinicians, AI/ML specialists, and ETAI leaders. We have organized a comprehensive 10-week long training plan that includes: 1) a well-thought-out applicant re- cruitment plan and mentee appointment protocol; 2) a mentor team with strong commitment from UCLA School of Medicine, medical informatics, and computational medicine faculty that follow our mentor selection processes; and 3) a customized curriculum tailoring each mentee to completing their training. Overall, our training platform aims to overcome anxiety surrounding biomedical AI/ML, build community trust, and empower trainees exploring biomedical AI/ML topics with entry at ground zero. Each trainee can design their personalized curriculum and complete AI education at their own pace. The majority of the curriculum is conducted via an e-learning platform, complemented by 1-on-1 mentorship and A&Q consultation hours. Each mentee will partner with the SWD Core to customize training plans and design their personalized curriculum, which enables them to complete AI edu- cation in their own space and to carry out AI/ML projects in real-world scenarios. The mentor teams will be responsible for creating milestone reports for each mentee to steer a successful career trajectory. The goal of this supplemental activity is to support URiM medical professionals to acquire necessary understanding and skills in AI/ML and to enable them to be the driving force to advance AI strategies in modern healthcare.

NIH的数据科学战略计划阐明了一个宏伟而雄心勃勃的目标，以增强 数据科学劳动力并吸引代表性不足的少数民族社区。确实，道德的愿景 只有在我们的股份时，才能实现由现代AI/ML医疗创新支持的公平社会 持有人包括所有社区的代表。在NIH的多样性目标中，此应用程序 旨在通过关键领导人促进生物医学AI/ML社区进行长期变化以促进 我们在促进多样化的下一代多学科人群的成长方面的使命 是启用桥梁2ai的驱动力的老虎。简而言之，我们认识到生物医学的重大挑战 AI/ML教育限制了现代AI/ML在医疗保健和生物医学创新中的广泛采用。 在我们的劳动力中，人们普遍缺乏对道德和可信赖的AI（ETAI）的了解 围绕AI/ML应用的公众焦虑融合。这些问题扼杀了潜在的影响 这些AI/ML技术。因此，我们建议建立Bridge2AI-Enable Scholar Award。 成功实施AI/ML策略至关重要的是新兴的医学人数不足 （Urim）;这些专业人士（例如医学生，临床研究员，护士，医生）在他们的 医学专业，并致力于接受AI/ML的进一步培训并提高临床实践。我们的 拟议的Bridge2AI-Enable Scholar奖将为有针对性的AI/ML培训提供多达15个URIM医学专业的培训 - 有望成为未来领导者的Sionals推动医疗保健中的AI/ML创新。这个乌里姆富集 活动将包括由临床医生，AI/ML专家和ETAI领导者组成的指定导师团队。我们 已经组织了一项全面的为期10周的培训计划，其中包括：1）经过深思熟虑的申请人 诉讼计划和受训者任命方案； 2）一支拥有加州大学洛杉矶分校学校坚定承诺的导师团队 遵循我们的导师选择过程的医学，医学信息学和计算医学教师； 3）定制的课程定制每个受训者，以完成他们的培训。总体而言，我们的培训平台 旨在克服围绕生物医学AI/ML的焦虑，建立社区信任并授权受训者探索 生物医学AI/ML主题，以零地面入口。每个学员都可以设计其个性化课程， 按照自己的节奏完成AI教育。大多数课程是通过电子学习平台进行的 以一对一的指导和A＆Q咨询时间进行补充。每个受训者将与SWD核心合作 定制培训计划并设计其个性化课程，这使他们能够完成AI EDU- 在自己的空间中阳离子，并在实际情况下进行AI/ML项目。导师团队将是 负责为每个受训者创建里程碑报告，以引导成功的职业轨迹。目标 这种补充活动是为了支持Urim医学专业人员获得必要的理解和 AI/ML的技能，使它们成为推动现代医疗保健中AI策略的驱动力。