LLMS at the Bedside – Improving Patient Education Materials and Informed Consent in Neuromodulation

Artificial intelligence and large language models (LLMs) are reshaping neuromodulation at every level of care - from how patients first learn about their diagnosis, to how adaptive stimulation algorithms respond in real time, to how Medicare determines whether a therapy will be covered at all. This rapid integration is generating profound new capabilities, but also profound new questions. This session examines the growing role of AI and LLMs across the neuromodulation care continuum through a neuroethics lens. Speakers will present evidence on LLM-assisted patient education materials and informed consent processes; review the Boston Scientific Illuminate platform as a real-world example of AI-driven adaptive therapy; explore the Medicare WISeR model as a case study in algorithmic prior authorization and its downstream effects on access; and critically examine the data infrastructure that makes AI-powered neuromodulation possible - along with the privacy, equity, and autonomy concerns that come with it. Throughout, the session centers on patient perspectives: Who consents to their neural data being used? Who benefits when AI optimizes a therapy - and who may be left behind? What obligations do clinicians, industry, and payers bear when algorithmic systems mediate care? Attendees will leave with a richer understanding of both the promise and the ethical stakes of AI in neuromodulation, and with practical frameworks for responsible integration.