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

Decision Support for Health Professionals (1210) Machine Learning (1501)

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 (27) Tweetations (5) Metrics

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  18. Lin S, Nateqi J, Weingartner-Ortner R, Gruarin S, Marling H, Pilgram V, Lagler F, Aigner E, Martin A. An artificial intelligence-based approach for identifying rare disease patients using retrospective electronic health records applied for Pompe disease. Frontiers in Neurology 2023;14 View
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Books/Policy Documents

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