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I agree with all points with respect to static EMRs including NLP efforts.

The cadence, uniformity and alignment of event stores to underlying pathways does pose an opportunity (but there's so little research and I suspect Brian didn't have access to this space). An EMR is a projection/point in time snapsot of these events (basically API calls). There's also inherent natural labels because inferences are evaluated against an actual pathway.

Specifically speaking about intra-episodic inferences -- longitudinal predictions (over several episodes -- or a patient life time) becomes wildly inaccurate. There's a lot of research to demonstrate this no matter which models are used.