AI Insights - Ep.5: Forecasting Mental Health with ML, Deep Learning and LLMs

In this episode of The Cisco AI Insights Podcast, hosts Rafael Herrera and Sónia Marques are joined by Cisco’s Technical Leader in Machine Learning Engineering Leticia Fernandes to explore the groundbreaking study, "A Comparative Study of Traditional Machine Learning, Deep Learning, and Large Language Models for Mental Health Forecasting Using Smartphone Sensing Data," which evaluates how different AI architectures analyze complex smartphone behavioral data to predict future mental health states. The discussion delves into the intricacies of forecasting mental health changes using five years of data from the College Experience Sensing dataset, highlighting how deep learning models, particularly transformer architectures, outperform traditional machine learning and Large Language Models by effectively leveraging personalized user behavior to identify subtle anomalies that could signal declining mental health, while also addressing the challenges of data imbalance and the inherent limitations of LLMs in processing high-dimensional, non-textual temporal sequences. A special thank you to the researchers from The Singapore University of Technology and Design, that developed this month's paper. If you are interested in reading the paper yourself, please visit this link:

You can listen to AI Insights - Ep.5: Forecasting Mental Health with ML, Deep Learning and LLMs online on Radio and Podcast. Open the player on this page to stream the available audio.

AI Insights - Ep.5: Forecasting Mental Health with ML, Deep Learning and LLMs is an episode from Cisco Podcast Network by Cisco Podcast Network.

This episode is 00:28:01 long.

This episode was published on May 29, 2026.

Yes. Use the heart button on the episode page to add it to your favorite episodes list.

Yes. This page shows related episodes from Cisco Podcast Network when more episodes are available from the podcast feed.