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

Decision Support for Health Professionals (1185) Machine Learning (1465)

Published on in Vol 6, No 4 (2018): Oct-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11301, first published .
Utilization of Electronic Medical Records and Biomedical Literature to Support the Diagnosis of Rare Diseases Using Data Fusion and Collaborative Filtering Approaches

Utilization of Electronic Medical Records and Biomedical Literature to Support the Diagnosis of Rare Diseases Using Data Fusion and Collaborative Filtering Approaches

Utilization of Electronic Medical Records and Biomedical Literature to Support the Diagnosis of Rare Diseases Using Data Fusion and Collaborative Filtering Approaches

Authors of this article:

Feichen Shen1 Author Orcid Image ;   Sijia Liu1 Author Orcid Image ;   Yanshan Wang1 Author Orcid Image ;   Andrew Wen1 Author Orcid Image ;   Liwei Wang1 Author Orcid Image ;   Hongfang Liu1 Author Orcid Image
Article Authors Cited by (25) Tweetations (5) Metrics

Journals

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  16. Parolo S, Tomasoni D, Bora P, Ramponi A, Kaddi C, Azer K, Domenici E, Neves-Zaph S, Lombardo R. Reconstruction of the Cytokine Signaling in Lysosomal Storage Diseases by Literature Mining and Network Analysis. Frontiers in Cell and Developmental Biology 2021;9 View
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Books/Policy Documents

  1. Hersh W. Information Retrieval: A Biomedical and Health Perspective. View