The broader impact/commercial potential of this I-Corps project is the development of digital interventions to detect and deliver early treatment recommendations for advanced cardiac disease. Through the use of artificial intelligence, it is possible address one of the most pressing healthcare burdens in the United States by detecting trajectories of chronic heart disease early. As a result, this technology would enable multiple applications including, but not limited to, reductions in healthcare-related costs, chronic disease burden, specialist care gaps, and time to treatment. This proposed technology may deliver a new era of software as a digital therapeutic, an area traditionally reserved for non-chronic conditions.
This I-Corps project is based on the development of a software platform using neural network models that leverage the use of biomarkers coupled with clinical vitals. Combining molecular and clinical data applied through natural experimentation, has made it is possible to understand the state changes of heart disease. Through the use of deep neural network learning, the proposed project goal is to make algorithms think and understand as humans by replicating the human brain connection and focusing on learning state changes rather than task-specific algorithms. Previous work on molecular profiling paired with clinical data within the realm of heart transplantation has yielded promising results in creating new sub-diagnosis as well as new artificial intelligence-guided therapy optimization protocols.
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.
