Cargando…
Asthma Exacerbation Prediction and Risk Factor Analysis Based on a Time-Sensitive, Attentive Neural Network: Retrospective Cohort Study
BACKGROUND: Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patients’ quality of life. However, efficient methods that can help identify personalized risk factors and make early predictions are lacking. OBJECTIVE: T...
Autores principales: | Xiang, Yang, Ji, Hangyu, Zhou, Yujia, Li, Fang, Du, Jingcheng, Rasmy, Laila, Wu, Stephen, Zheng, W Jim, Xu, Hua, Zhi, Degui, Zhang, Yaoyun, Tao, Cui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7428917/ https://www.ncbi.nlm.nih.gov/pubmed/32735224 http://dx.doi.org/10.2196/16981 |
Ejemplares similares
-
Time-sensitive clinical concept embeddings learned from large electronic health records
por: Xiang, Yang, et al.
Publicado: (2019) -
Med-BERT: pretrained contextualized embeddings on large-scale structured electronic health records for disease prediction
por: Rasmy, Laila, et al.
Publicado: (2021) -
Recurrent neural network models (CovRNN) for predicting outcomes of patients with COVID-19 on admission to hospital: model development and validation using electronic health record data
por: Rasmy, Laila, et al.
Publicado: (2022) -
428. Deep-Learning Based Predictive Model for Patients with Positive MRSA Cultures Using Time-Series Electronic Health Records
por: Nigo, Masayuki, et al.
Publicado: (2022) -
Public Perception Analysis of Tweets During the 2015 Measles Outbreak: Comparative Study Using Convolutional Neural Network Models
por: Du, Jingcheng, et al.
Publicado: (2018)