By: Scott J. Mendelson, PhD, M.D., Vice Chief of Neurology, Access TeleCare
Artificial intelligence has moved past the hype stage in stroke and neurological care. The question we hear most from hospital partners isn’t “Is AI real?” but “Where does it actually help us right now?”
The short answer: Today, AI adds real value in diagnosis, imaging, and documentation. In the near future, the biggest opportunities will likely come from:
- Prehospital triage;
- Care coordination; and
- Quality oversight.
The longer answer is that AI doesn’t succeed because of one flashy algorithm — it succeeds when health systems build the right workflows around it, prioritizing integration, governance, measurement, and human oversight.
AI for Stroke Diagnosis: Faster Recognition and Clinical Action
In the emergency department, time is everything. AI tools can now flag potential large vessel occlusions (LVOs) or intracerebral hemorrhages (ICH) within minutes and push images straight to neurologists, interventionalists, and transfer centers.
That orchestration matters. Instead of waiting for a phone tree to play out, the right people get the right images at the right time. The key, though, is not just having alerts — it’s having accountability: who acknowledges the alert, who takes the next step, and how the team measures improvement.
AI should never replace human decision-making in stroke — but it can give clinicians the head start they need to act decisively.
AI in Stroke Imaging: CT and CTA Analysis That Improves Outcomes
Imaging is where neurological AI tools are most mature. Today’s FDA-cleared tools can detect bleeds, identify suspected LVOs, and generate perfusion maps to estimate salvageable tissue.
Some platforms are even moving into the angio suite, giving interventional teams perfusion data without ever leaving the table. The clinical math is simple: earlier recognition + shared imaging + faster mobilization = better patient outcomes.
But again, the difference isn’t in the algorithm alone — it’s in whether hospitals build tight workflows around it. Who gets notified, how fast, and what do they do next? That’s where measurable gains happen.
AI Documentation in Neurology: Reducing Clinician Burden with Ambient Notes
Anyone who’s managed an acute stroke knows the paperwork load. Ambient “AI scribe” tools can now listen (with consent), generate a draft note, and pre-fill required stroke-program elements like NIHSS, treatment risks, or antithrombotic plans.
These tools don’t eliminate the need for clinician oversight, but they can dramatically cut the time spent on documentation. The biggest wins come when they’re aligned with stroke quality reporting so the note doesn’t just help the clinician — it also feeds what the quality team needs, automatically.
Prehospital AI for Stroke: EMS Triage and 911 Call Recognition
The next breakthroughs are likely to come before patients ever hit the ED doors.
- Dispatcher recognition: AI trained on 911 call audio is starting to show promise in picking up acute neurological symptoms faster than humans alone.
- EMS triage: Pairing telemedicine in the ambulance with AI-assisted screening could improve hospital selection, reduce mis-triage, and shorten transfer times for thrombectomy candidates.
This is still early territory — but with strong governance and safety checks, these pilots could pay off big.
AI for Neurology Program Quality and Care Coordination
AI doesn’t just live in the spotlight. Behind the scenes, it can help assemble transfer packets, surface missing data, reconcile time stamps, and even flag cases for peer review. Think of these tools as a co-pilot — not replacing clinical oversight, but nudging teams toward more consistent, reliable care.
The Future of AI in Stroke and teleNeurology
AI in neurology is no longer “future tech.” It’s already helping teams:
- See the right images sooner
- Mobilize the right people faster
- Spend less time documenting and more time treating
The hospitals seeing success, however, aren’t just buying software — they’re hard-wiring these tools into parallel workflows with clear roles and safety checks.
That’s how AI becomes more than buzz — it becomes faster treatment and better outcomes.
