A core friction in applying data science methods toward healthcare is the competing desire to make a positive impact via implementation and also being sufficiently skeptical of the rigor your work. This isn’t some abstract thought experiment: despite a very large amount of investment¹ and energy in publication² there are very few ML/AI systems in place in healthcare institutions. As a data scientist working in healthcare myself, I know how difficult it is to get stakeholders meaningfully invested in implementation. Not to mention the bevvy of complications involved in the field itself³ ⁴ ⁵. …

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