Top 10 AI Terms Every Medical Communicator Should Know

One lament I’ve been hearing pretty consistently from medical communication colleagues is how technical discussions about artificial intelligence (AI) can be, with terms that go undefined and examples that are not relevant to our field or industries.

To address these concerns for my colleagues in medical communication (freelance or in-house), I’m adding a glossary of AI terms for medical writers here on the DCC Cyber site.

Today I’m sharing the first 10 entries, the “Top 10” entries that really are salient to anyone, but with examples in the medical context.

The main difference between this glossary and content you will find at other resources (even ones for writers) is that I arrange the terms in an order of importance for medical writers and editors and write the related entries to be consistent with one another. For example, algorithm, training, model, and application are related terms that are part of a process, so they are written together using the same example.

In the interest of time, I’m not sure I’ll be able to provide examples for the entire list as I go, but I’ve added them to these first 10 to get things started.

So, without further ado, the Top 10 AI Terms Every Medical Communicator Should Know.

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