Collaborative Research: CISE-MSI: RCBP-RF: CNS: ESD4CDaT - Efficient System Design for Cancer Detection and Treatment

机器学习（ML）的应用变得越来越流行，不仅在医疗保健和医药领域，而且在其他领域解决现实生活中的问题。机器学习推动不同领域的研究者进行跨学科的研究，获得新的发现。在贾维斯基督教大学（JCU）（原贾维斯基督教学院（JCC））和克莱顿州立大学（CSU），两家机构的研究人员团队在进行机器学习和物联网（IoT）在癌症检测、预测和治疗方面的应用研究方面有着日益增长的兴趣。为了实现双方研究人员的利益，建立了一个合作研究项目。该项目的主要目标是促进合作，探索机器学习和物联网应用于癌症检测、预测和治疗的新研究方向。为了支持目标的推进并使团队受益，该项目旨在1)开发基于机器学习的新型算法，以构建检测、识别和预测癌细胞生长和治疗的软件， 2)将新型机器学习算法与廉价的物联网硬件结合起来，以实现癌症研究的数据收集，3)开发基于智能相机的应用程序，用于视觉皮肤癌数据收集和分析。4)为两家合作机构提供本科和研究生课程项目或论文，用于医学成像和癌症治疗应用ML和IoT的研究和培训。该项目的主要成果是：1)HBCU的学生和教师与主要为少数民族服务的研究所之间的合作；2)癌症诊断、预测和治疗的研究数据收集和分析；3)本科和研究生在机器学习和物联网应用软件设计领域的课程进步；4)通过CISE-MSI核心基金资助，为两所机构之间未来持续的合作研究和教育建立更坚实的基础。该奖项部分由传统黑人学院和大学卓越研究（HBCU-EiR）和CISE少数民族服务机构（CISE MSI）研究扩展计划资助。该奖项反映了美国国家科学基金会的法定使命，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 applications of Machine Learning (ML) become more popular for solving real life problems not only in healthcare and medicines but also in other fields. ML pushes investigators from different fields to conduct interdisciplinary research and obtain new discovery. There are mutually growing interests among team of researchers at two institutions in conducting research on the applications of ML and Internet of Things (IoT) for cancer detections, predictions, and treatments at Jarvis Christian University (JCU) (formerly Jarvis Christian College (JCC)) and Clayton State University (CSU). To realize the interests of the investigators from both universities, a collaborative research project is established.The primary goal of the project is to catalyze collaborations and explore new research directions in the applications of ML and IoT for cancer detections, predictions, and treatments. To support the advancement of the goal and benefit the team, the project aims to 1) develop novel ML based algorithms to build software to detect, identify, and predict cancer cell growths and treatments,  2) infuse novel ML algorithms with the inexpensive IoT hardware to enable data collection for the cancer research, 3) develop smart camera based apps for visual skin cancer data collections and analysis, and 4) offer undergraduate and graduate course projects or theses for the two collaborative institutions to conduct research and training in applied ML and IoT for medical imaging and cancer treatments. The major outcomes of the project are 1) collaboration among students and faculty of an HBCU with a predominantly minority serving institute, 2) research data collections and analysis for cancer diagnosis, prediction, and treatment, 3) curriculum advancements at undergraduate and graduate levels in the areas of software design for ML and IoT applications, and 4) build stronger foundations of continuing future collaborative research and education between the two institutions via CISE-MSI core funding grants. This award was funded in part by the Historically Black Colleges and University Excellence in Research (HBCU-EiR) and the CISE Minority Serving Institutions (CISE MSI) Research Expansion programs.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.