An independent study on machine learning and artificial intelligence (AI) was released by the McKinsey Global Institute (MGI) in June 2017, focusing on the following central question: “Is artificial intelligence the next digital frontier, and if so, are businesses ready for it?”
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Using Support Vector Machines
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Machine Learning and Healthcare: Breast Cancer Diagnosis
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Shruti Kaushik1,a, Abhinav Choudhury1,b, Nataraj Dasgupta2,c, Sayee Natarajan2,d, Larry A. Pickett2,e, and Varun Dutt1,f
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A patient’s journey as they navigate and choose from the many treatments and options available to them is highly unique. The sheer number of variables can be overwhelming. Aggregate patient journey information is locked in APLD (anonymous patient level data) sources like claims, prescription, and EMR data sets. Logically sifting through multiple multi-billion row data sets looking for actionable insights is important for today’s pharmaceutical manufacturers. It requires the most leading edge possible data infrastructures to handle at scale.
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