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Citing this Article

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Published on 10.10.18 in Vol 6, No 4 (2018): Oct-Dec

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

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

According to Crossref, the following articles are citing this article (DOI 10.2196/11301):

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

  1. Faviez C, Chen X, Garcelon N, Neuraz A, Knebelmann B, Salomon R, Lyonnet S, Saunier S, Burgun A. Diagnosis support systems for rare diseases: a scoping review. Orphanet Journal of Rare Diseases 2020;15(1)
  2. Cohen AM, Chamberlin S, Deloughery T, Nguyen M, Bedrick S, Meninger S, Ko JJ, Amin JJ, Wei AJ, Hersh W, Ramagopalan SV. Detecting rare diseases in electronic health records using machine learning and knowledge engineering: Case study of acute hepatic porphyria. PLOS ONE 2020;15(7):e0235574
  3. Alam M, Banwell C, Olsen A, Lokuge K. Patients’ and Doctors’ Perceptions of a Mobile Phone–Based Consultation Service for Maternal, Neonatal, and Infant Health Care in Bangladesh: A Mixed-Methods Study. JMIR mHealth and uHealth 2019;7(4):e11842
  4. Brasil S, Pascoal C, Francisco R, dos Reis Ferreira V, A. Videira P, Valadão G. Artificial Intelligence (AI) in Rare Diseases: Is the Future Brighter?. Genes 2019;10(12):978
  5. Li X, Wang Y, Wang D, Yuan W, Peng D, Mei Q. Improving rare disease classification using imperfect knowledge graph. BMC Medical Informatics and Decision Making 2019;19(S5)
  6. Shen F, Zhao Y, Wang L, Mojarad MR, Wang Y, Liu S, Liu H. Rare disease knowledge enrichment through a data-driven approach. BMC Medical Informatics and Decision Making 2019;19(1)