Vastly improved health and longer lifespans in our population brings with it chronic disorders arising from cumulative genetic, environmental and metabolic factors. These complex disease processes include neurovascular disorders, dementia and cancer, which collectively represent a third of total deaths in the United States. At the same time, the increasing sophistication of medical diagnostics has yielded an exponential growth in the density and complexity of aggregated healthcare data. New genomic and metabolomic technologies for example enable us to capture heterogeneous disease pathophysiology on a molecular level with pristine detail.
Together, these factors provide an unprecedented opportunity to study differences in disease among individuals and provide tailored care to patients. Indeed the very complexity of these disease states directly translates into their very personal nature. Today, the challenge posed to the healthcare system is to translate the richness of multidimensional data streams into individualized measures for disease prevention, diagnosis and treatment. To address this challenge, the mission of the UCI Precision Health through Artificial Intelligence (PHAI) Initiative is to leverage machine learning technology to transform population-through molecular-level data into personalized health solutions, and work to make these tools available to providers and patients around the world.
UCI PHAI embraces the following key principles:
- Clinical utility. This work is driven first and foremost by practical day-to-day clinical needs rather than model systems. Importantly, solutions should mature beyond initial prototypes into deployable tools that solve real-world problems.
- Scalability. At UCI, PHAI is investing in resources and developing key technology platforms to rapidly scale the development, testing and deploying of machine learning tools across every medical specialty.
- Education. The next generation of leaders will need to understand and engage new technologies including machine learning solutions in healthcare. To accommodate this emerging demand, PHAI actively invests in comprehensive and cross-disciplinary educational opportunities across the undergraduate, graduate and post-graduate communities.
- Cross-trained experts. The PHAI team is led by clinician scientists with unique expertise across key domains including computer sciences, informatics, clinical medicine and biomolecular research.
- Inter-disciplinary research. A key goal of the PHAI initiative is to foster collaborative interaction across the UCI academic disciplines and empower engagement between new teams to inspire healthcare innovation.
We look forward to sharing our progress.
Leslie Thompson, Donald Bren Professor and Chancellor's Professor in the School of Medicine and School of Biological Sciences
Peter Chang, Assistant Professor in the School of Medicine
Daniel Chow, Assistant Professor in the School of Medicine
Suzanne Sandmeyer, Vice Dean for Research and Professor in the School of Medicine