Cargando…
Interpretable Conditional Recurrent Neural Network for Weight Change Prediction: Algorithm Development and Validation Study
BACKGROUND: In recent years, mobile-based interventions have received more attention as an alternative to on-site obesity management. Despite increased mobile interventions for obesity, there are lost opportunities to achieve better outcomes due to the lack of a predictive model using current existi...
Autores principales: | Kim, Ho Heon, Kim, Youngin, Park, Yu Rang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8088842/ https://www.ncbi.nlm.nih.gov/pubmed/33779574 http://dx.doi.org/10.2196/22183 |
Ejemplares similares
-
Weight Loss Trajectories and Related Factors in a 16-Week Mobile Obesity Intervention Program: Retrospective Observational Study
por: Kim, Ho Heon, et al.
Publicado: (2022) -
Development of a Recurrent Neural Network Model for Prediction of Dengue Importation
por: Kim, Sun-Young, et al.
Publicado: (2019) -
Influence of graphical weights’ interpretation and filtration algorithms on generalization ability of neural networks applied to digit recognition
por: Kusy, Maciej, et al.
Publicado: (2011) -
Real-Time Clinical Decision Support Based on Recurrent Neural Networks for In-Hospital Acute Kidney Injury: External Validation and Model Interpretation
por: Kim, Kipyo, et al.
Publicado: (2021) -
A Circuit-Based Neural Network with Hybrid Learning of Backpropagation and Random Weight Change Algorithms
por: Yang, Changju, et al.
Publicado: (2016)