NRT-FW-HTF: NSF Traineeship in the Advancement of Surgical Technologies

外科技术的快速变化对未来的工程人员提出了新的要求。例如，未来的工程师将创造智能手术器械，使用人工智能和机器学习来做出临床决策的自主机器人，以及增强外科医生性能和能力的工具。这将需要技能和知识的融合，以跨越技术，监管，道德和社会障碍，创造安全，成功地应对现代挑战的技术。大多数研究生工程课程擅长教授各自学科的基本原理。然而，研究生工程课程往往缺乏培训，使学生能够超越自己的学科，从事融合研究，不仅涉及其他工程师，而且还涉及其他STEM领域，医学，商业和法律的专业人士。通过与这些其他学科的合作，本次培训将为工程师的专业形成提供更全面和创新的方法，以影响先进手术技术的未来。 授予杜克大学的国家科学基金会研究培训（NRT）将培养硕士和博士。工程学、计算机科学、数据科学和外科技术等跨学科领域的学生。 该项目预计将培训总共230名学生，包括30名由NRT资助的工程、计算机科学、数学、科学与社会和统计学专业的受训人员。该实习的愿景是为工程和计算机科学研究生提供一个新的研究和培训框架，使其能够进入其他学科，从而设计出先进的外科技术，在整个开发和测试过程中整合医疗提供者、社会、最终用户和患者的需求。拟议的实习模式结合了基于课堂、基于研究和专业发展的活动，导致四个核心学习成果：（1）共同的知识基础;（2）跨多个融合学科的学科专业知识;（3）在外科技术研究和开发的最前沿的翻译经验;（4）专业发展机会，为学生在外科技术领域的学术和行业职业生涯做好准备。拟议方案的一个具体新奇是使用与微型设计挑战相互关联的局部引物，受训者将跟随外科医生，使用当前的手术工具和机器人，并在机器人技术，手术，机器学习，快速原型，伦理，知识产权和医疗法方面学习知识引物;这些活动的目的是让学生迅速掌握多元化的知识基础和所需的专业发展。培训生还将收到利益相关者的反馈，如外科医生和来自行业的外部董事会成员，以提供进一步的专业发展。NSF研究培训生（NRT）计划旨在鼓励开发和实施大胆的，新的潜在变革模式，用于STEM研究生教育培训。该计划致力于通过创新的、基于证据的、与不断变化的劳动力和研究需求相一致的综合培训模式，在高优先级的跨学科或融合研究领域对STEM研究生进行有效培训。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

Rapid changes in surgical technologies have created new demands on the future engineering workforce. For example, future engineers will create intelligent surgical instruments, autonomous robots that use artificial intelligence and machine learning to make clinical decisions, and tools that augment the performance and capabilities of surgeons. This will require a convergence of skillsets and knowledge to traverse technological, regulatory, ethical, and societal hurdles to create technologies that safely and successfully meet modern challenges. Most graduate engineering programs excel at teaching the fundamental tenets of their respective disciplines. However, graduate engineering curricula often lack the training that enables students to transcend their disciplines and engage in convergent research that involves not just other engineers, but also professionals from other STEM fields, medicine, business, and law. By engaging with these other disciplines, this traineeship will provide a more holistic and innovative approach for the professional formation of engineers to impact the future of advanced surgical technologies. This National Science Foundation Research Traineeship (NRT) award to Duke University will train Master’s and Ph.D. students in the interdisciplinary fields of engineering, computer science, data science, and surgical technologies. This project anticipates training a total of 230 students, including 30 NRT-funded trainees from Engineering, Computer Science, Math, Science and Society, and Statistics. The vision for this traineeship is to provide a new research and training framework for engineering and computer science graduate students to access other disciplines and thereby design advanced surgical technologies that integrate medical provider, societal, end-user, and patient needs throughout development and testing.The proposed traineeship model combines classroom-based, research-based, and professional development activities completed concurrently over two years, leading to four core learning outcomes: (1) a common knowledge base; (2) subject expertise across multiple, convergent disciplines; (3) a translational experience at the forefront of surgical technology research and development; and (4) professional development opportunities that prepare students for both academic and industry-based careers in surgical technology. A specific novelty of the proposed program is the use of topical primers interconnected with mini design challenges in which trainees will shadow a surgeon, use current surgical tools and robots, and take knowledge primers in robotics, surgery, machine learning, rapid prototyping, ethics, intellectual property, and medical law; these activities are designed to enable students to acquire a diverse knowledge base and necessary professional development quickly. Trainees will also receive feedback from stakeholders such as surgeons and external board members from industry to provide further professional development.The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.