Artificial Intelligence: Implementing a Vision for Precision Medicine and Health
BLACKSBURG, VA. May 11, 2017 – Studying human diseases is the equivalent of solving a massive and dynamic jigsaw puzzle with pieces that are constantly changing shape. A team involving researchers from the Nutritional Immunology and Molecular Medicine Laboratory (NIMML) at Virginia Tech and the Biomedical and Translational Informatics (BTI) Institute at Geisinger Health System are working together to advance precision medicine by integrating clinical data, artificial intelligence (AI) systems, and advanced machine-learning (ML) methods. In a new study, the collaborative team of experts have developed new computational methods to stratify stroke patients in an emergency setting, paving the way to data-driven triage process with higher fidelity.
The rich, longitudinal data warehouse of the Geisinger Health System (GHS) has detailed electronic health records (EHR) of over 3 million active participants. This rich data is one of the major strengths that allowed Geisinger to be selected to participate in the national Precision Medicine Initiative (PMI) Cohort Program with the goal of improving the ability to prevent and treat diseases based on individual differences in lifestyle, environment, and genetics.
Geisinger, a pioneering institution in personalized and precision medicine, partners with multiple industry and academic institutions, including NIMML, to conduct research in precision medicine to improve patient care. Geisinger’s collaboration with Regeneron Genetics Center, the DiscovEHR project, catalyze genomic discovery and precision medicine by coupling high-throughput exome sequencing to longitudinal EHRs of participants in Geisinger’s MyCode Community Health Initiative, with thus far over 60,000 sequenced.
The existing collaboration between NIMML and Geisinger capable of capturing human diversity and variation in the context of infectious and immune-mediated diseases, which has the potential to drive the identification of novel biomarkers of disease activity and therapeutic targets, plus the development of safer, more effective personalized treatments for widespread human diseases with unmet clinical needs.
“My resolve to implement a revolutionary vision for precision medicine is the driving force that defines and underpins this successful collaboration. By focusing on a unique iterative integration of large-scale clinical record mining using new AI systems, informatics analyses and computer modeling. As opposed to the one-size-fits-all approach that dominates healthcare today, NIMML and GHS are making tangible progress toward the personalized, individual treatment of human diseases.” Says Dr. Bassaganya-Riera, Director of the NIMML and CEO of BioTherapeutics.
At its core, AI is a complex computer algorithm that replaces the traditional rule-based strategy with a data-driven approach capable of learning from positive and negative experiences. AI algorithms are driving the future of precision medicine and provide better healthcare support for diverse and dynamic patient populations. On average, the EHR of a four-year patient contains about 32 petabytes of data. The application of AI in medicine will leverage the volume and exponential growth of clinical data to translate clinical information into new unforeseen insights for safer, more effective and cost-efficient personalized healthcare.
“Advanced machine-learning (ML) methods will be driving the next generation of personalized medicine, at the clinical and genomic levels; however, these methods and their outcomes will have an added value if we let models actively learn from experts and experts learn from models with the ability to refine and validate the predictions that enable discovering hidden relationships and novel associations. Our team has applied AI successfully to develop a data-driven triage process for classifying stroke patients. Ongoing collaborative studies are also applying these same AI methods successfully in infectious and immune-mediated diseases.” Says Dr. Abedi, a researcher at the Geisinger Health System and adjunct faculty member at NIMML.
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