A significant portion of my time at Massachusetts General Hospital (MGH) was spent analyzing a cohort of 65,099 individuals diagnosed with type 2 diabetes mellitus (T2DM). During these training years as a research fellow (2013 to 2016), I, along with my colleagues at MGH and Harvard, implemented a variety of predictive modeling methods as well as incorporated natural language processing techniques to better understand diseases and their complications. We focused on cardiovascular disease, liver disease, and insomnia. This T2DM cohort contained complete clinical details as well as demographics of patients who received care at MGH or Brigham and Women’s…
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