Neurologists

Right now, computers are starting to help neurologists, but they don’t do the whole job. For example, AI tools can flag things on brain scans: one program approved by the FDA can quickly alert specialists to likely stroke on a CT scan ^[1]. Other research shows an AI model can read EEGs (brainwave tests) as accurately as experts ^{[2] [2]}.

Some hospitals use software that listens to doctor-patient conversations and helps write the visit note ^[3]. There’s also research where AI has learned to tell apart normal and diseased muscle signals (from EMG tests) with high accuracy ^[4]. Still, most things need a human.

No program can examine a patient, feel reflexes, or decide who to refer to (specialists like therapists or surgeons). Computers can’t replace the judgment and communication of a neurologist. And for complicated lab results or brain tests, doctors must make sense of it all.

So far, AI is more of a helpful assistant than a replacement.

Neurology faces a shortage of doctors, so there’s interest in helpful AI tools ^{[3] [3]}. AI could help overworked neurologists by handling routine tasks and alerting them to urgent problems sooner. But adoption will be careful.

Medical tools must prove they are safe and follow strict privacy rules ^[3]. For example, the FDA clears AI programs only as aids – doctors must still review and confirm any diagnosis ^{[1] [3]}. Clinicians worry about mistakes or missing details if they rely too much on AI ^{[2] [3]}.

Getting new tech also costs time and money to train staff and set up. Despite these challenges, AI in neurology is promising: it can speed up some work and may help reach patients who have less access to specialists ^{[3] [3]}. In the end, the human skills of listening, examining, and understanding people will stay very important, with AI serving as a computer helper to make care better.