.HeartBobH and Jenine John, a cardiologist and machine-learning research fellow, discuss what you need to know about AI and machine learning in healthcare and where to find some helpful resources. CardioTwitter
That's an extremely important question to ask. We're still in the early days of using AI and trying to figure out the pitfalls and how to avoid them. I think it's important to ask along the way, for each study, what is going on here. Is this a model that we can trust and rely on?
We also need to understand that in healthcare, we can't necessarily accept the black box. We need explainability and interpretability, to get an understanding of the variables that are used, how they're being used within the algorithm, and how they're being applied.to predict who was at risk for medical complications and high healthcare expenditures. The model did well, so they used the model to determine who should get additional resources to prevent these complications.
I'm always intrigued. When you talk to your friends in the tech world, they say,"Well, we do this all the time. We do A/B testing." They just constantly run through algorithms through A/B testing, which is a randomized study. How come we don't do more of that in healthcare?I think it's complicated because we don't have the systems to do that effectively.
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