I work in healthcare and one thing that's always top of mind for me is that that the data we work with is only (generally) indicative of the physicians'/billers

I work in healthcare and one thing that's always top of mind for me is that that the data we work with is only (generally) indicative of the physicians'/billers' best guess. So - say we get a bunch of diagnosis codes from a hospital. Codes are generally added in via medical billers after a patient is discharged, based on the physicians input and other data on the patient record. So at this point the data in which you generally work with has gone through two different humans, who used their (best attempt) subjective viewpoint for this patient. This generally works fine for a lot of common conditions, evident conditions, so things like heart attacks, fractures, and so on. But for things that are complex, like sepsis leading to more evident conditions, the data may not necessarily capture that sepsis even occurred. Not to say this is a unique problem to healthcare, but something that's not talked about often. A lot of the data we train and model on is based on a human's best guess, which may in some ways be limiting given really complex, dynamic processes.