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

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.