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

Secondary Use of Clinical Data for Research and Surveillance (375) Ethics, Privacy, and Legal Issues (494) Big Data (245)

Published on in Vol 6, No 2 (2018): Apr-Jun

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9455, first published .
Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources

Privacy-Preserving Predictive Modeling: Harmonization of Contextual Embeddings From Different Sources

Authors of this article:

Yingxiang Huang1 Author Orcid Image ;   Junghye Lee2, 3, 4 Author Orcid Image ;   Shuang Wang1 Author Orcid Image ;   Jimeng Sun5 Author Orcid Image ;   Hongfang Liu6 Author Orcid Image ;   Xiaoqian Jiang1 Author Orcid Image
Article Authors Cited by (10) Tweetations (3) Metrics

Journals

  1. 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 View
  2. Wang Y, Liu S, Afzal N, Rastegar-Mojarad M, Wang L, Shen F, Kingsbury P, Liu H. A comparison of word embeddings for the biomedical natural language processing. Journal of Biomedical Informatics 2018;87:12 View
  3. Tiwari P, Colborn K, Smith D, Xing F, Ghosh D, Rosenberg M. Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation. JAMA Network Open 2020;3(1):e1919396 View
  4. Mandair D, Tiwari P, Simon S, Colborn K, Rosenberg M. Prediction of incident myocardial infarction using machine learning applied to harmonized electronic health record data. BMC Medical Informatics and Decision Making 2020;20(1) View
  5. Huang Y, Jiang X, Gabriel R, Ohno-Machado L. Calibrating predictive model estimates in a distributed network of patient data. Journal of Biomedical Informatics 2021;117:103758 View
  6. 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 View
  7. Lee M, Kim S, Kim H, Lee J. Technology Opportunity Discovery using Deep Learning-based Text Mining and a Knowledge Graph. Technological Forecasting and Social Change 2022;180:121718 View
  8. Li M, Lin Y, Chen H, Aparasu R. An unsupervised embedding harmonization system for privacy-preserving data mining in healthcare. IISE Transactions on Healthcare Systems Engineering 2024;14(1):1 View
  9. 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 View
  10. 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 View