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Joint Program Committee-1 (JPC-1)/Medical Simulation and Information Sciences (MSIS) Research Program -- Utilizing Machine Learning and Artificial Intelligence for Medical Training Needs (MACH Learning) Award
Proposals/Applications to the FY17 JPC-1/MSIS MACH Learning Award are being solicited for the Defense Health Agency (DHA) J9, Research and Development Directorate, by the U.S. Army Medical Research Acquisition Activity (USAMRAA). As directed by the Office of the Assistant Secretary of Defense for Health Affairs (OASD[HA]), the DHA manages the Defense Health Program (DHP) Research, Development, Test, and Evaluation (RDT&E) appropriation. The U.S. Army Medical Research and Materiel Command (USAMRMC) Congressionally Directed Medical Research Programs (CDMRP) provides Defense Medical Research and Development Program (DMRDP) management support for DHP core research program areas, including the JPC-1/MSIS. This BAA/Funding Opportunity and subsequent awards will be managed by CDMRP with strategic oversight from JPC-1/MSIS.
The mission of the JPC-1/MSIS is to explore the implications of models, technology and informatics for medical education/training, and for the provision, management, and support of healthcare services in the military. The JPC-1/MSIS plans, coordinates, and oversees a responsive world-class, tri-Service science and technology program focused on two areas of research: (1) improving military medical training through medical modeling, simulation, and educational training tools; and (2) improving the use and sharing of health-related data for better strategic planning, process development, and software applications. The JPC-1/MSIS Medical Modeling, Simulation and Training Steering Committee provided the strategy for which this Broad Agency Announcement/Funding Opportunity’s topic was conceived.
Per guidance from DoD Instruction (DoDI) 5000.02,1 the outcomes of research funded by this Broad Agency Announcement/Funding Opportunity will be used to better understand optimal algorithms and models to predict advancement of individuals as they are acquiring skills but also to assist in analyzing skill decay and assist in refresher training through machine learning and artificial intelligence approaches. These proposed machine learning models with artificial intelligence approaches would have substantial public purpose applications as an adjunct, objective way to provide additional information to instructors and faculty to advance students (medical, nursing, emergency medical technicians, etc.), as well as residents and licensed professionals, to more appropriate courses as those students acquire skills or the professionals refresh their own skills.
MACH Learning is a line of research that supports the Medical Readiness Initiative (MRI) under the JPC-1/MSIS Medical Simulation and Training Technologies portfolio. The JPC-1/MSIS MRI focuses on research and ultimately the development of medical training methods, technologies, systems, and competency assessment tools for the attainment and sustainment of medical readiness for the military and the public. MRI also focuses on research methodologies, techniques, and tools that will allow for ethical, accurate, and appropriate pre-intervention rehearsal for medical providers with the input of authorized personalized medical information into simulation models.
The FY17 JPC-1/MSIS MACH Learning Award is intended to support research projects to develop machine learning/artificial intelligence modeling that can be used as predictive models for early detection of needed medical training during the acquisition of skills as well as refresher training. The research project should focus on an effective training surveillance system model that can address training requirements in the military medical community and that also has applicability for public purpose. The research must be able to mine a variety of training data reports in order to analyze training outcomes to determine level of competence/proficiency and model and predict training effectiveness as well as aligning training outcomes with that of curricula objectives in real time.
• Pre-Proposal/Pre-Application Submission Deadline: February 3, 2017
• Invitation to Submit a Proposal/Application: March 10, 2017
• Proposal/Application Submission Deadline: May 12, 2017
Independent extramural investigators at all academic levels (or equivalent) are eligible to submit applications.
• The maximum period of performance is 30 months. The proposed pilot study must be included within the proposed 30-month Statement of Work plan and, at a minimum, must be 12 months in duration. • The anticipated total costs budgeted for the entire period of performance will not exceed $1,600,000. Indirect costs are to be budgeted in accordance with the organization’s negotiated rate. No budget will be approved by the Government exceeding $1,600,000 total costs or using an indirect rate exceeding the organization’s negotiated rate. • All direct and indirect costs of any subaward (subgrant or subcontract) must be included in the total direct costs of the primary award. • Option periods may be used on contracts. • The applicant may request the entire maximum funding amount for a project that may have a period of performance less than the maximum 30 months.