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Exploring the Potential of Electroencephalography Signal–Based Image Generation Using Diffusion Models: Integrative Framework Combining Mixed Methods and Multimodal Analysis

Exploring the Potential of Electroencephalography Signal–Based Image Generation Using Diffusion Models: Integrative Framework Combining Mixed Methods and Multimodal Analysis

The architecture integrates a simplified U-Net model, denoted as ∈prior (It, t, E), where It represents the noisy CLIP embedding at a specific diffusion step t. The classifier-free guidance method refined the diffusion model by conditioning it on a specific EEG input E. This approach synchronized the outputs of both the conditional and unconditional models. The final model equation was expressed as follows: . (3).

Chi-Sheng Chen, Shao-Hsuan Chang, Che-Wei Liu, Tung-Ming Pan

JMIR Med Inform 2025;13:e72027

Temporal Dynamics of Subtle Cognitive Change: Validation of a User-Friendly Multidomain Digital Assessment Using an Alcohol Challenge

Temporal Dynamics of Subtle Cognitive Change: Validation of a User-Friendly Multidomain Digital Assessment Using an Alcohol Challenge

This includes conditions with primary pathology anchored in the central nervous system (CNS—ie, neurodevelopmental, neuropsychiatric, and neurodegenerative disorders, as well as trauma), as well as CNS impairment secondary to other drivers of brain dysfunction (eg, “brain fog” following chemotherapy, chimeric antigen receptor T-cell, or radiation therapy, COVID-19).

John Frederick Dyer, Florentine Marie Barbey, Ayan Ghoshal, Ann Marie Hake, Bryan J Hansen, Md Nurul Islam, Judith Jaeger, Rouba Kozak, Hugh Marston, Mark Moss, Viet Nguyen, Rebecca Louise Quinn, Leslie A Shinobu, Elizabeth Tunbridge, Brian Murphy, Niamh Kennedy

J Med Internet Res 2025;27:e55469

Detection of Depressive Symptoms in College Students Using Multimodal Passive Sensing Data and Light Gradient Boosting Machine: Longitudinal Pilot Study

Detection of Depressive Symptoms in College Students Using Multimodal Passive Sensing Data and Light Gradient Boosting Machine: Longitudinal Pilot Study

The data used in this study were part of a randomized controlled trial examining a just-in-time mobile health intervention (ie, relational savoring) [55,56] designed to prevent loneliness (the study by Nguyen et al [unpublished data, 2024] provides an overview of the design of the intervention component of the study).

Jessica L Borelli, Yuning Wang, Frances Haofei Li, Lyric N Russo, Marta Tironi, Ken Yamashita, Elayne Zhou, Jocelyn Lai, Brenda Nguyen, Iman Azimi, Christopher Marcotullio, Sina Labbaf, Salar Jafarlou, Nikil Dutt, Amir Rahmani

JMIR Form Res 2025;9:e67964