[HTML][HTML] Integration of artificial intelligence and wearable internet of things for mental health detection

W Wang, J Chen, Y Hu, H Liu, J Chen… - International Journal of …, 2024 - Elsevier
Abstract The integration of Artificial Intelligence (AI) and Wearable Internet of Things (WIoT)
for mental health detection is a promising area of research with the potential to revolutionize …

Affective computing in the era of large language models: A survey from the nlp perspective

Y Zhang, X Yang, X Xu, Z Gao, Y Huang, S Mu… - arxiv preprint arxiv …, 2024 - arxiv.org
Affective Computing (AC), integrating computer science, psychology, and cognitive science
knowledge, aims to enable machines to recognize, interpret, and simulate human emotions …

A comprehensive survey on GNN-based anomaly detection: taxonomy, methods, and the role of large language models

Z Yuan, Q Sun, H Zhou, M Shao, X Fu - International Journal of Machine …, 2025 - Springer
With the rapid growth of data volumes in real-world applications, anomaly detection has
become a crucial task across various scenarios. Anomalies are generally defined as data …

Enhanced Large Language Models for Effective Screening of Depression and Anxiety

JM Liu, M Gao, S Sabour, Z Chen, M Huang… - arxiv preprint arxiv …, 2025 - arxiv.org
Depressive and anxiety disorders are widespread, necessitating timely identification and
management. Recent advances in Large Language Models (LLMs) offer potential solutions …

DAIC-WOZ: On the Validity of Using the Therapist's prompts in Automatic Depression Detection from Clinical Interviews

S Burdisso, E Reyes-Ramírez, E Villatoro-Tello… - arxiv preprint arxiv …, 2024 - arxiv.org
Automatic depression detection from conversational data has gained significant interest in
recent years. The DAIC-WOZ dataset, interviews conducted by a human-controlled virtual …

Multimodal Depression Detection with Contextual Position Encoding and Latent Space Regularization

E Zhang, C Poellabauer - openreview.net
Clinical interviews are the gold standard for detecting depression, and previous work using
multimodal features from participants' audio, transcribed text, and video have shown …