AI outputs can be useful as a starting point, but they often fail in predictable ways for residents dealing with traumatic brain injuries after local crashes.
Common reasons the estimate can drift from reality:
- The timeline gets flattened. TBI symptoms often worsen or become clearer after the initial visit—especially when people return to work before their symptoms stabilize.
- Documentation quality matters more than the label. Two people can have the same diagnosis term, but one has consistent follow-ups (and clearer functional notes) while the other has gaps.
- Insurance evaluation isn’t math-only. Adjusters weigh liability evidence and causation arguments, not just symptom categories.
If you’re using an AI “range,” treat it like a checklist—not a promise.


