S&AS: INT: COLLAB: An Intelligence-Driven Patient Care Approach to Reduce Medical Errors (I-CARE)

想象一下，在不久的将来，一个需要手术的病人将吞下一个小型移动机器人，它可以在没有任何外部伤口或疼痛的情况下自主执行手术。这类机器人有可能通过提供一个不受限制的移动平台来可视化、操纵和手术治疗组织，从而使最先进的手术概念成为现实。该项目的战略还将利用围绕机器人和计算机科学的兴奋，并将其与调查人员用于教育创新和推广的卓越基础设施相结合，为学生提供新的、鼓舞人心的教育体验。最后，项目成果可以广泛影响其他一些将受益于开发的新方法的领域，包括搜索和救援、建筑和维护以及远程成像，这些领域的环境是动态的或经过反复检查而发生变化。该项目的目标是从根本上了解智能驱动的患者护理方法的认知和适应需求，以减少医疗差错。实现这种智能物理系统将允许增强医生的能力。如果考虑到未来的手术室，可以想象从包括外科医生、辅助医疗技术人员和麻醉师在内的所有医务人员那里收集数据并与其共享的场景。此外，人工智能可以被用来在病人护理中寻找看不见的模式。只有建立一种新的范式，包括具有嵌入式智能和自主功能的医疗设备，才有可能实现未来的手术室。这样的智能物理系统将从支持人员、传感器和诊断中收集知识，并解释医生的意图，并实时提供建议和诊断反馈。为了提供这种方法的真实评估，该项目将专注于机器人胶囊内窥镜检查，目的是对传统的胃肠病学程序产生立竿见影的影响。为了实现这一目标，该项目涉及三个研究目标：第一个目标专注于机器人胶囊内窥镜的感知和控制；第二个目标制定感知和诊断支持要求，以增强医生的表现；第三个目标集成多模式、多标签、时态数据分析，以支持智能医生的支持。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Imagine that in the near future a patient needing surgery will swallow a small mobile robot that can autonomously perform the procedure without any external incisions or pain. Such robots have the potential to make state-of-the-art surgical concepts a reality by providing an unconstrained mobile platform to visualize, manipulate and surgically treat tissue. The project's strategy will also harness the excitement surrounding robotics and computer science, and leverage it with the investigators' exceptional infrastructure for education innovation and outreach to provide new, inspirational educational experiences for students. Finally, the project outcomes can broadly impact a number of other areas that would benefit from the developed novel methodologies, including search and rescue, construction and maintenance, and remote imaging, where the environment is dynamic or changes upon repeated inspection.The goal of this project is to gain a fundamental understanding of the cognition and adaptation needs of an intelligence-driven patient care approach to reduce medical errors. Realizing such an intelligent physical system would allow for augmenting physician capabilities. If one considers an operating room of the future, one can imagine scenarios where data is collected from, and shared with, all medical personnel including the surgeon, the supporting medical technicians, and anesthesiologists. In addition, artificial intelligence could be harnessed to look for unseen patterns in patient care. This operating room of the future will only be possible by establishing a new paradigm that includes medical devices with embedded smart and autonomous features. Such an intelligent physical system would gather knowledge from support personnel, sensors and diagnostics, and interpret physician intent and provide suggestions and diagnostic feedback in real-time. To provide real-world evaluation of this approach, the project will focus on robotic capsule endoscopy, with an intent to have immediate impact in conventional gastroenterology procedures. In pursuit of this goal, this project addresses three research objectives: the first objective focuses on robotic capsule endoscopy perception and control; the second objective formulates the perception and diagnostic support requirements to augment physician performance; and the third objective integrates multimodal, multi-label, temporal data analytics for intelligent physician support.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.