Neurology® Podcast January 2026 Recall: Topics on Artificial Intelligence in Neurology
Jan 2, 2026
Stephen Marche, a novelist and columnist, shares insights on the implications of AI in writing and neurology. Sándor Beniczky discusses SCORE-AI's role in automating EEG interpretations, enhancing diagnostic workflow. David T. Jones presents StateViewer, a machine-learning tool that boosts diagnostic accuracy in neurodegenerative disorders. Adam Rodman highlights the potential of large language models in clinical reasoning while stressing the importance of clinician involvement. The conversation weaves through the transformative impact of AI on medicine and the necessity for human connection.
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How Large Language Models Work
- Large language models are massive next-word predictors built from transformer architectures trained on huge text corpora.
- Stephen Marche emphasizes they produce coherence but have no inherent fact-checking or true understanding.
Treat LLMs As First-Draft Assistants
- Use LLMs as first-draft tools rather than final authors for personal or scholarly writing.
- Expect to revise outputs thoroughly and verify facts before claiming authorship.
Hallucination Risk Is Real
- LLMs frequently hallucinate: they generate coherent but potentially false statements.
- Users must fact-check outputs because these models lack inherent truth verification.