Cargando…
Sequential Data–Based Patient Similarity Framework for Patient Outcome Prediction: Algorithm Development
BACKGROUND: Sequential information in electronic medical records is valuable and helpful for patient outcome prediction but is rarely used for patient similarity measurement because of its unevenness, irregularity, and heterogeneity. OBJECTIVE: We aimed to develop a patient similarity framework for...
Autores principales: | Wang, Ni, Wang, Muyu, Zhou, Yang, Liu, Honglei, Wei, Lan, Fei, Xiaolu, Chen, Hui |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8778569/ https://www.ncbi.nlm.nih.gov/pubmed/34989682 http://dx.doi.org/10.2196/30720 |
Ejemplares similares
-
Measurement and application of patient similarity in personalized predictive modeling based on electronic medical records
por: Wang, Ni, et al.
Publicado: (2019) -
Study on the semi-supervised learning-based patient similarity from heterogeneous electronic medical records
por: Wang, Ni, et al.
Publicado: (2021) -
Patient Representation From Structured Electronic Medical Records Based on Embedding Technique: Development and Validation Study
por: Huang, Yanqun, et al.
Publicado: (2021) -
Predicting Organization Performance Changes: A Sequential Data-Based Framework
por: Song, Meiqi, et al.
Publicado: (2022) -
Exploring the Relationship Between Anxiety, Depression, and Sleep Disturbance Among HIV Patients in China From a Network Perspective
por: Wang, Ni, et al.
Publicado: (2021)