Planning Grant: Engineering Research Center for Computing Yourself to be Better - Engineering for Revolutionizing Medical Decision-making (CYBER-MD)

工程研究中心的规划赠款竞争是作为ERC计划内的试点招标运行。 ERC竞赛不要求提供规划赠款，但旨在培养团队规划融合的、中心规模的工程研究的能力。提高家庭、长期护理机构和医院医疗保健的质量和效率，对患者和整个社会都变得越来越重要。虽然目前医疗保健领域的两大趋势--远程医疗和数字医疗--正在取得进展，但它们只是触及了问题的表面，而不是解决问题的根本原因。为了彻底改变医疗保健服务，我们需要一个全面的生物物理患者模型，即“数字孪生”，它将数据流、医生笔记/评估和病史与严格的计算引擎融合在一起，可以对未来的患者健康/福祉进行概率预测。然后，医疗保健提供商将能够将传统知识/培训与数字孪生的“数据决策”姿态相结合，同时与患者合作，以最佳方式评估他们的健康状况，评估选项，预测未来的健康状况，并优化患者的预后。这项计划补助金的目的是吸引和汇聚工程师，数据科学家，教育工作者，艺术家，医学专家，医院，咨询公司，数字健康公司以及卫生和政府机构的广泛利益相关者社区，以公开讨论和确定最紧迫的工程研究，教育和需要解决的外展差距，以彻底改变医疗决策和个性化医疗。一旦ERC成立，该团队将与利益相关者密切合作，以确定医疗保健中的当前问题，设计和构建工程解决方案，并在仔细评估其有效性后分阶段部署这些解决方案。通过这些活动，将实现真正的个性化医疗，其中网络物理医疗保健监测可以针对特定患者进行量身定制，因为他们可以在早期发现风险，而不是在严重并发症出现时。此外，CYBER-MD ERC的教育和外展计划将积极招募女性、代表性不足和经济上处于弱势的个人，用于研究和培训未来几代多学科、融合的科学家和工程师。今天的医疗实践仅为临床医生提供有限的历史患者数据，医生往往依赖过时的培训和轶事经验来最好地照顾他们的患者。然而，由于各种疾病的肿瘤学广泛重叠，漏诊和误诊仍然是一个主要问题。CYBRE-MD ERC的愿景是建立一个网络物理创新中心，在生物物理建模，成像，传感，数据科学，数据可视化和概率风险评估方法学方面的工程突破共同革新了医疗诊断/治疗过程，以改善患者的预后。这一概念的基石是一个“数字孪生”，它与患者一起诞生，然后随着时间的推移不断更新，包括从生物识别到疾病/损伤评估到诊断图像/结果到后续治疗的新数据流。数字孪生模型不仅为存储患者健康信息提供了一种新的数据架构，还提供了变革性的健康评估和预测分析功能，使医生和患者能够共同努力改善患者的健康、福祉和结果。CYBER-MD本质上是跨学科的，涵盖了科学，技术，工程，艺术和数学（STEAM）以及医学的所有分支。该规划补助金将召集不同的专家，以汇集在最终的战略实施，确定重点研究的重大挑战，确定相关的主题领域，与利益相关者沟通，教育，设计创新和广泛实施的教育/推广工作，并组装最有能力和多样化的团队，支持这个跨学科的NSF ERC。计划中的活动直接支持聚合研究，这是应对这一跨越STEAM、医学、医疗保健和公共健康/福祉领域的总体重大挑战所必需的。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The Planning Grants for Engineering Research Centers competition was run as a pilot solicitation within the ERC program. Planning grants are not required as part of the full ERC competition, but intended to build capacity among teams to plan for convergent, center-scale engineering research.Improving the quality and efficiency of healthcare - at home, in long-term care facilities, and in hospitals - is becoming ever more important for patients and the society at large. Although the two current trends in healthcare - telemedicine and digital medicine - are making headway, they only scratch the surface of the problem as opposed to dealing with the root cause. To revolutionize healthcare delivery, we need a comprehensive biophysical patient model, namely a "digital twin", that fuses data streams, doctor notes/assessments, and medical histories with a rigorous computational engine that can make probabilistic predictions of future patient health/well-being. Healthcare providers will then be able to integrate traditional knowledge/training with the "data-to-decision" posture of the digital twin, while working with the patient, to best assess their health, evaluate options, predict future health, and optimize patient outcomes and prognosis. The aim of this Planning Grant is to engage and converge a broad stakeholder community of engineers, data scientists, educators, artists, medical specialists, hospitals, consulting firms, digital health firms, and health and government agencies to openly discuss and identify the most urgent engineering research, education, and outreach gaps that need to be addressed for revolutionizing medical decision-making and personalized medicine. Once the ERC is established, the team will partner closely with stakeholders to identify current issues in medical care, design and build engineering solutions, and deploy these solutions in phases after careful assessment of their effectiveness. It is through these activities that truly personalized medicine will be achieved, where cyber-physical healthcare monitoring can be tailored to specific patients as they are identified early at risk versus when severe complications unfold. Furthermore, the education and outreach initiatives of the CYBER-MD ERC will actively recruit women, underrepresented, and economically disadvantaged individuals for research and training future generations of multidisciplinary, convergent scientists and engineers.Healthcare practice today only provides clinicians with limited amounts of historic patient data, and doctors tend to rely on outdated training and anecdotal experiences to best care for their patients. However, given the broad overlap in symptomatology across various diseases, missed diagnosis and misdiagnosis remains a major problem. The vision of the CYBRE-MD ERC is to establish a cyber-physical innovation hub, where engineering breakthroughs in bio-physical modeling, imaging, sensing, data science, data visualization, and probabilistic risk assessment methodologies collectively revolutionize the medical diagnostic/treatment process for improving patient outcomes. The cornerstone of this concept is a "digital twin" that is born and then evolves with the patient while constantly being updated over time with new data streams ranging from biometrics to illness/injury assessments to diagnostic images/results to subsequent treatments. The digital twin not only presents a new data architecture for storing patient health informatics, but it also provides transformative health assessment and predictive analytic capabilities that enable doctors and patients to work together to improve patient health, well-being, and outcomes. CYBER-MD is inherently transdisciplinary and spans the entire spectrum of science, technology, engineering, arts, and mathematics (STEAM) as well as all branches of medicine. This Planning Grant will convene diverse experts to converge on a final strategic implementation, define focused research grand challenges, identify relevant thematic areas, communicate with stakeholders, educate, devise innovative and broadly implementable education/outreach efforts, and assemble the most competent and diverse team that underpins this transdisciplinary NSF ERC. The activities planned directly support convergent research, which is of utmost necessity for tackling this overarching grand challenge that spans the fields of STEAM, medicine, healthcare, and public health/well-being.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.