Cargando…
End-to-End Depression Recognition Based on a One-Dimensional Convolution Neural Network Model Using Two-Lead ECG Signal
PURPOSE: Depression is a common mental illness worldwide and has become an important public health problem. The current clinical diagnosis of depression mainly relies on the doctor’s experience and subjective diagnosis, which results in the low diagnostic efficiency and insufficient objectivity of d...
Autores principales: | Zang, Xiaohan, Li, Baimin, Zhao, Lulu, Yan, Dandan, Yang, Licai |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8819200/ https://www.ncbi.nlm.nih.gov/pubmed/35153641 http://dx.doi.org/10.1007/s40846-022-00687-7 |
Ejemplares similares
-
End-to-End Convolutional Neural Network Model to Detect and Localize Myocardial Infarction Using 12-Lead ECG Images without Preprocessing
por: Uchiyama, Ryunosuke, et al.
Publicado: (2022) -
Frontal Alpha Complexity of Different Severity Depression Patients
por: Zhao, Lulu, et al.
Publicado: (2020) -
End-to-end speech emotion recognition using a novel context-stacking dilated convolution neural network
por: Tang, Duowei, et al.
Publicado: (2021) -
Using Convolutional Neural Network and a Single Heartbeat for ECG Biometric Recognition
por: AlDuwaile, Dalal A., et al.
Publicado: (2021) -
Automatic Triage of 12‐Lead ECGs Using Deep Convolutional Neural Networks
por: van de Leur, Rutger R., et al.
Publicado: (2020)