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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"

Wael Farhan, Zhimu Wang, Yingxiang Huang, Shuang Wang, Fei Wang, Xiaoqian Jiang

JMIR Med Inform 2016 (Nov 25); 4(4):e39 

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
    CrossRef
  2. 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
    CrossRef
  3. 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
    CrossRef
  4. 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
    CrossRef
  5. Pokharel S, Zuccon G, Li X, Utomo CP, Li Y. Temporal tree representation for similarity computation between medical patients. Artificial Intelligence in Medicine 2020;108:101900
    CrossRef
  6. 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
    CrossRef
  7. Kim Y, El-Kareh R, Sun J, Yu H, Jiang X. Discriminative and Distinct Phenotyping by Constrained Tensor Factorization. Scientific Reports 2017;7(1)
    CrossRef
  8. 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
    CrossRef
  9. 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)
    CrossRef
  10. Qureshi MA, Qureshi KN, Jeon G, Piccialli F. Deep learning-based ambient assisted living for self-management of cardiovascular conditions. Neural Computing and Applications 2022;34(13):10449
    CrossRef
  11. Lee JM, Hauskrecht M. Modeling multivariate clinical event time-series with recurrent temporal mechanisms. Artificial Intelligence in Medicine 2021;112:102021
    CrossRef
  12. Lee T, Lee J, Jun C. Bilingual autoencoder-based efficient harmonization of multi-source private data for accurate predictive modeling. Information Sciences 2021;568:403
    CrossRef
  13. Getzen E, Ungar L, Mowery D, Jiang X, Long Q. Mining for equitable health: Assessing the impact of missing data in electronic health records. Journal of Biomedical Informatics 2023;139:104269
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  14. B. V. VR, Jayanthila Devi A. Design and Development of Efficient Model to Predict Neurodegenerative Disorders Using Advanced LSTM: A Review of Literature. International Journal of Case Studies in Business, IT, and Education 2022;:521
    CrossRef
  15. Yoo J, Lee J, Min JY, Choi SW, Kwon J, Cho I, Lim C, Choi MY, Cha WC. Development of an Interoperable and Easily Transferable Clinical Decision Support System Deployment Platform: System Design and Development Study. Journal of Medical Internet Research 2022;24(7):e37928
    CrossRef
  16. Liu X, Wang H, He T, Liao Y, Jian C. Recent Advances in Representation Learning for Electronic Health Records: A Systematic Review. Journal of Physics: Conference Series 2022;2188(1):012007
    CrossRef
  17. Memarzadeh H, Ghadiri N, Samwald M, Lotfi Shahreza M. A study into patient similarity through representation learning from medical records. Knowledge and Information Systems 2022;64(12):3293
    CrossRef
  18. Lee T, Kim S, Jun C, Lee J. Word2vec-Based Efficient Privacy-Preserving Shared Representation Learning for Federated Recommendation System in a Cross-Device Setting. SSRN Electronic Journal 2023;
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  19. Liang Z, Zhang Z, Chen H, Zhang Z. Disease prediction based on multi-type data fusion from Chinese electronic health record. Mathematical Biosciences and Engineering 2022;19(12):13732
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  20. Yue Z, Yan T, Xu H, Liu Y, Hong Y, Chen G, Xie T, Tao L. A systematic review on the state-of-the-art strategies for protein representation. Computers in Biology and Medicine 2023;152:106440
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  21. V S A, Bizotto BLS, Sathiyanarayanan M. Human Intelligence and Value of Machine Advancements in Cognitive Science A Design thinking Approach. Journal of Machine and Computing 2023;:159
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  22. ZEHRAOUI F, Sendi N, Abchiche-Mimouni N. MS-LSTMEA: Predicting Clinical Events for Hypertension Using Multi-Sources LSTM Explainable Approach. SSRN Electronic Journal 2022;
    CrossRef
  23. Li M, Lin Y, Chen H, Aparasu RR. An unsupervised embedding harmonization system for privacy-preserving data mining in healthcare. IISE Transactions on Healthcare Systems Engineering 2024;14(1):1
    CrossRef
  24. Lee T, Kim S, Lee J, Jun C. Word2Vec-based efficient privacy-preserving shared representation learning for federated recommendation system in a cross-device setting. Information Sciences 2023;651:119728
    CrossRef
  25. Lee T, Kim S, Lee J, Jun C. HarmoSATE: Harmonized embedding-based self-attentive encoder to improve accuracy of privacy-preserving federated predictive analysis. Information Sciences 2024;662:120265
    CrossRef

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

  1. Jana S, Ray S, Adhikary P, Banerjee TP. Cognitive Computing in Human Cognition. 2020. Chapter 9:91
    CrossRef
  2. Zhang T, Chen M, Bui AAT. Artificial Intelligence in Medicine. 2020. Chapter 31:348
    CrossRef
  3. Malygina T, Drokin I. Artificial Intelligence and Natural Language. 2018. Chapter 10:98
    CrossRef
  4. Bulgarelli L, Núñez-Reiz A, Deliberato RO. Leveraging Data Science for Global Health. 2020. Chapter 4:55
    CrossRef
  5. Mansourvar M, Wiil UK, Nøhr C. Emerging Technologies in Computing. 2020. Chapter 9:126
    CrossRef