The Key to Transforming Medicine is Recognizing it as a Knowledge-Processing Discipline
It's now clear that the response to the Coronavirus pandemic was fundamentally crippled by a lack of measurement, data aggregation and limitations of current analytic methods. This was only the most recent and vivid demonstration of a structural weakness in biomedicine that has massively slowed both discovery research from cancer biology to neuroscience and translation of basic science to the practice of medicine. This department of Biomedical Informatics (DBMI) was founded in 2005 specifically to address that weakness. Whether it is the development of machine learning techniques to find therapeutics for rare diseases, to enabling patients to share computable versions of their own medical record for researchers and their own care, or to identifying cancer pathology in brain tissue intra-operatively, DBMI researchers are focusing on the intersection between computational methods, basic biology and clinical practice by accelerate biomedicine. Most importantly, we have long recognized that the greatest opportunity and challenge is to use our healthcare systems as living laboratories to drive research.
Just as the biomedical research enterprise and clinical care establishment has lagged in using computational tools and methods to address their bottlenecks in data and knowledge processing, DBMI recognizes that an analogous delay exists in biomedical education, whether in medical school or graduate school. Therefore DBMI faculty have developed doctoral and masters programs to address these educational gaps, as well as medical school classes (see AISC 610).
Academia may be a useful crucible for a substantial part of the biomedical informatics research agenda but ignoring the relevant efforts in the growing ecosystem of consumer-focused and industry-driven developments is intellectually limiting and massively reduces the opportunity to positively impact human health. DBMI faculty have embraced like-minded and forward looking companies and business leaders in our research mission. Conversely, we taken upon ourselves educating our students about these broader opportunities (see our Entrepreneurs Salon for an example).
Before I completed my medical training, during my doctoral research in artificial intelligence, it became clear to me just how much we could improve the care of our patients using these automated tools to transform both the care of patients and return clinicians to a more patient facing and less clerical role. More of this perspective is shared in a recent piece I wrote with colleagues at Google for the New England Journal of Medicine,Machine Learning in Medicine. Many of our faculty have gravitated to our department before of a natural affinity to this perspective and therefore it drives many of our newest research initiatives.
—Zak Kohane, Chair
DBMI in 3 Minutes
Four founding faculty members and the executive director give a brief overview.