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This paper proposes a lightweight CNN classifier that uses Fourier-Bessel Series Expansion with Euclidean Distance (FBSE-ED) to represent EEG signals as images, achieving 93.60% accuracy in predicting the outcome of rTMS depression therapy, outperforming both EEG-specific and pretrained deep learning models.
A study from Southeast University found that GLP-1 drugs like Ozempic reverse depression-like behavior in mice by promoting growth of Lactobacillus delbrueckii, which produces endocannabinoids that reduce stress effects.
This paper presents a method for fine-tuning LLMs to predict PHQ-9 depression severity scores directly from transcripts of conversations with an AI mental health application, achieving strong correlation with clinical thresholds using a augmented dataset of 6,283 users.