In practice, an “AI misdiagnosis” concern usually isn’t that a computer made a diagnosis like a person would. It’s more commonly about how information was routed, interpreted, or documented.
In and around Bowling Green, patients often move between settings—primary care, urgent care, ER visits, imaging appointments, and follow-ups. Along that path, automated tools may:
- Flag a risk level or suggest likely conditions
- Influence which tests are ordered first
- Affect how imaging is queued or reviewed
- Generate draft notes that clinicians then finalize
A claim may be strongest when the record shows that a tool’s output conflicted with objective findings, or when the team failed to escalate, re-check, or communicate critical results promptly.


