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Citing this Article

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Published on 25.11.16 in Vol 4, No 4 (2016): Oct-Dec

This paper is in the following e-collection/theme issue:

Works citing "A Predictive Model for Medical Events Based on Contextual Embedding of Temporal Sequences"

According to Crossref, the following articles are citing this article (DOI 10.2196/medinform.5977):

(note that this is only a small subset of citations)

  1. Khan A, Zubair S. Longitudinal Magnetic Resonance Imaging as a Potential Correlate in the Diagnosis of Alzheimer Disease: Exploratory Data Analysis. JMIR Biomedical Engineering 2020;5(1):e14389
  2. Li Z, Roberts K, Jiang X, Long Q. Distributed learning from multiple EHR databases: Contextual embedding models for medical events. Journal of Biomedical Informatics 2019;92:103138
  3. Ashfaq A, Sant’Anna A, Lingman M, Nowaczyk S. Readmission prediction using deep learning on electronic health records. Journal of Biomedical Informatics 2019;97:103256
  4. Min X, Yu B, Wang F. Predictive Modeling of the Hospital Readmission Risk from Patients’ Claims Data Using Machine Learning: A Case Study on COPD. Scientific Reports 2019;9(1)
  5. Santiso S, Pérez A, Casillas A. Smoothing dense spaces for improved relation extraction between drugs and adverse reactions. International Journal of Medical Informatics 2019;128:39
  6. Tang F, Xiao C, Wang F, Zhou J. Predictive modeling in urgent care: a comparative study of machine learning approaches. JAMIA Open 2018;1(1):87
  7. Huang Y, Lee J, Wang S, Sun J, Liu H, Jiang X. Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources. JMIR Medical Informatics 2018;6(2):e33
  8. Kim Y, El-Kareh R, Sun J, Yu H, Jiang X. Discriminative and Distinct Phenotyping by Constrained Tensor Factorization. Scientific Reports 2017;7(1)

According to Crossref, the following books are citing this article (DOI 10.2196/medinform.5977)

  1. Malygina T, Drokin I. Artificial Intelligence and Natural Language. 2018. Chapter 10:98