Is AI Ready to Be Used in Clinical Prediction in Neurology?

This lecture considered where clinical AI is useful now and what still limits prediction in neurology. Examples ranged from monitoring and prognosis to phenotyping, clinical text and fairness.

The question

Is the available evidence strong enough for AI predictions to influence neurological care?

Deck outline

• The relationship between AI, machine learning and deep learning
• Evidence and maturity in neurological monitoring
• Phenotyping, subtyping and prognosis
• Learning from unstructured clinical records
• Bias, fairness and equity
• Clinical utility and the remaining route to deployment

Take-away

Monitoring is closest to routine use; broader prediction requires stronger validation, attention to bias and evidence that the result is clinically useful.