Artificial Intelligence shaping the future of neurology practice

Area of Science:

• Neurology
• Artificial Intelligence
• Medical Diagnostics

Background:

• Neurology practice, established by Jean-Martin Charcot, faces evolving challenges.
• Artificial Intelligence (AI) presents significant opportunities to revolutionize neurological diagnostics and patient care.

Purpose of the Study:

• To explore the multifaceted applications of AI in contemporary neurology.
• To highlight AI's potential to enhance diagnostic accuracy and predictive capabilities in neurological disorders.

Main Methods:

• Review of current AI applications in neurological diagnostics, including stroke detection from CT/MRI scans.
• Analysis of AI's role in interpreting retinal scans for conditions like diabetic retinopathy and papilledema.
• Examination of AI's utility in electroencephalogram (EEG) interpretation for coma prognostication and seizure prediction.

Main Results:

• AI demonstrates capability in diagnosing stroke, detecting eye conditions, and interpreting EEGs.
• AI can predict the conversion of mild cognitive impairment to Alzheimer's dementia.
• AI facilitates the classification of neurodegenerative diseases using gait and handwriting analysis.

Conclusions:

• AI is poised to become an indispensable complementary tool in clinical neurology.
• Neurologists must adapt their perspective, viewing AI as an opportunity rather than a threat.
• The integration of AI promises to reshape the future landscape of neurological practice.