P08: Pre-Congress: AI in Neurophysiology

AI Tools in Clinical Neurophysiology

This course offers a focused introduction to artificial intelligence in Clinical Neurophysiology, addressing the appropriate use of machine learning, deep learning, and traditional statistical models (as competitors) in research and patient care using MATLAB and Python.

Emphasis is placed on data characteristics, model robustness, and clinical interpretability. The course also covers generative AI and large language models, highlighting ethical considerations, scientific journal policies, and best practices for the responsible and transparent integration of AI into neurophysiological research and clinical practice.

13:00-14:00 Practical, robust use of AI models for harmonization of clinical indexes and biomarkers in multicentric studies carried out in Clinical Neurophysiology
Verónica Henao Isaza

14:00-15:00 Practical, robust use of AI models for classification and prediction purposes in patients with Epilepsy based on clinical indexes and biomarkers
Benjamin H. Brinkmann

15:00-15:30 COFFEE BREAK

15:30-16:00 Regression vs. machine learning models in Matlab and Python ecosystems. What do you really need in Clinical Neurophysiology?
Antonio I. Triggiani

16.00-16:30 Ethical use of generative AI for writing a paper for Clinical Neurophysiology (Practice)
Claudio Babiloni

16:30-17:00 Quiz