Graph Neural Networks (GNNs) are computer algorithms that take data from graphs and uses relationships between the data points to make predictions or recommendations. Much like our own brains, neural networks connect and correlate information to generate possible patterns that can be helpful to a variety of fields, including infection control and prevention (IP). In IP, GNNs are being used to predict risk for healthcare acquired infections (HAIs) and make decisions about resource allocation. In today's post, we'll take a closer look at how this is being done.

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