AI for Behavioral Health – Intoxication Detection

AI for Behavioral Health: Machine Learning Approaches to Alcohol and Marijuana Intoxication Detection
Artificial intelligence is opening new frontiers in understanding human behavior through data. This talk explores how advances in machine learning and sensor analytics are transforming behavioral health assessment, with a focus on detecting alcohol and marijuana intoxication from motion and physiological data.
Drawing from interdisciplinary research across data science, healthcare, and behavioral studies, the session will walk through real-world AI pipelines—from data preprocessing and feature engineering to deep learning models like CNNs and Vision Transformers. Attendees will also gain insights into ethical and regulatory considerations, model interpretability, and deployment challenges.
The talk will highlight how AI-driven behavioral analytics can inform clinical care, improve community safety, and expand our broader understanding of human cognition and behavior.
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Speaker(s): Samuel,
Virtual: https://events.vtools.ieee.org/m/506597