Project Description

Cardiovascular disease affects more than 85.6 million Americans adults (>1 in 3), and the annual direct and indirect costs are estimated at $316.6 billion. Significant research efforts (e.g., biological experiments and clinical studies) have been undertaken to investigate cardiac pathologies and discover scientific knowledge for improving the efficiency and quality of cardiac care. However, biological and clinical experiments are not always feasible due to practical and ethical limitations. Computer modeling and simulations offer a powerful platform for virtual experiments, which can provide important insights that are difficult to discover with physical experiments alone. Such an approach has been iteratively interacted with in vitro experiments and clinical data to unravel disease mechanisms and develop hypotheses. For example, cardiac modeling and simulations can suggest physical experiments and help researchers find the root cause of cardiac disorders. Also, computer experiments can identify the most significant drugs that are the least likely to have side effects. However, guidelines of how to utilize computer modeling and simulations to suggest physical experiments are rarely seen and little work has been done to investigate how cardiac modeling can be used to aid the design of in vitro experiments. The objective of this undergraduate student research is to develop new methodologies to efficiently assess the reliability of cardiac models and suggest optimal design of physical experiments. This work will bring uncertainty quantification, global sensitivity analysis, design of experiments, and sequential optimization into a unified framework for efficient uncertainty analysis. The research methodology developed in this work will provide students with a unique opportunity to obtain multidisciplinary training in engineering and computational cardiology. The research findings will be disseminated through journal and conference publications. Dr. Yucheng Du is currently funded by NSF CMMI Award #1727487 on a related effort.