Cargando…
Automatic depression severity assessment with deep learning using parameter-efficient tuning
INTRODUCTION: To assist mental health care providers with the assessment of depression, research to develop a standardized, accessible, and non-invasive technique has garnered considerable attention. Our study focuses on the application of deep learning models for automatic assessment of depression...
Autores principales: | Lau, Clinton, Zhu, Xiaodan, Chan, Wai-Yip |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10308283/ https://www.ncbi.nlm.nih.gov/pubmed/37398577 http://dx.doi.org/10.3389/fpsyt.2023.1160291 |
Ejemplares similares
-
From Sound Perception to Automatic Detection of Schizophrenia: An EEG-Based Deep Learning Approach
por: Barros, Carla, et al.
Publicado: (2022) -
A deep learning-based model for detecting depression in senior population
por: Lin, Yunhan, et al.
Publicado: (2022) -
The applicability of the Beck Depression Inventory and Hamilton Depression Scale in the automatic recognition of depression based on speech signal processing
por: Hajduska-Dér, Bálint, et al.
Publicado: (2022) -
Dosing of Electrical Parameters in Deep Brain Stimulation (DBS) for Intractable Depression: A Review of Clinical Studies
por: Ramasubbu, Rajamannar, et al.
Publicado: (2018) -
Use of Machine Learning and Artificial Intelligence Methods in Geriatric Mental Health Research Involving Electronic Health Record or Administrative Claims Data: A Systematic Review
por: Chowdhury, Mohammad, et al.
Publicado: (2021)