ISPP 2015

Career Opportunities in Pharmacy
Man, Machine, and Medicine: Mass General Researchers Using AI

we started the clinical data science center with the intention of applying machine learning and other data science techniques to the art of Medicine so the intent is to be able to explore the integration of man and machine at this point of clinical care taking some of the data historically and using that data to actually create information in the machine so that we can see into the future what's happening with patients before the human has the idea that there are changes taking place so initial focus of the clinical data science center will be in diagnostics and that includes pathology genomics genetics and medical imaging as we extend beyond that we're looking at other areas that are also a survey horizontal solution essentially population health management or precision medicine we have very heterogeneous data and healthcare everything from a physician's note to genomic information MRI scans you name it we deal with a lot of types of data and so finding ways to take that data and boil meaning out of that is a significant challenge requires a high level of computational capability the importance of machine learning a deep learning for radiology is unquestioned I think the there's enormous amount opportunity for us to improve the efficiency of our work and the accuracy of our work through automation and semi automation perhaps there are patterns that I don't notice I don't see with my human eyes but machines can actually pick those out but that's where I see the process helping us on a day-to-day basis to increase our efficiency accuracy and productiveness in terms of how we practice as a molecular pathologists so my hope for our clinical data science center is that advances made through machine learning will improve the health of the populations we serve by reducing variation in how scans are performed images are interpreted and data is encoded from their scans it's hard to imagine a place within healthcare that deep learning won't touch I think that watching the way that machine learning and specifically deep learning has already began to affect health care I think in five to ten years it will be a Bic witness and it will be a critical tool in the physicians toolbox the same way and a stethoscope is the same way that our electronic health record is

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