Predicting the Reasons of Customer Complaints: A First Step Toward Anticipating Quality Issues of In Vitro Diagnostics Assays with Machine Learning

doi:10.2196/medinform.9960

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JMIR Medical Informatics

Impact Factor 3.2

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Published on 15.05.18 in Vol 6, No 2 (2018): Apr-Jun

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

Works citing "Predicting the Reasons of Customer Complaints: A First Step Toward Anticipating Quality Issues of In Vitro Diagnostics Assays with Machine Learning"

Stephane Aris-Brosou, James Kim, Li Li, Hui Liu

JMIR Med Inform 2018 (May 15); 6(2):e34

According to Crossref, the following articles are citing this article (DOI 10.2196/medinform.9960):

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

Tarekegn A, Ricceri F, Costa G, Ferracin E, Giacobini M. Predictive Modeling for Frailty Conditions in Elderly People: Machine Learning Approaches. JMIR Medical Informatics 2020;8(6):e16678
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Long GS, Hussen M, Dench J, Aris-Brosou S. Identifying genetic determinants of complex phenotypes from whole genome sequence data. BMC Genomics 2019;20(1)
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Hulsen T, Friedecký D, Renz H, Melis E, Vermeersch P, Fernandez-Calle P. From big data to better patient outcomes. Clinical Chemistry and Laboratory Medicine (CCLM) 2023;61(4):580
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JMIR Medical Informatics

Citing this Article

Published on 15.05.18 in Vol 6, No 2 (2018): Apr-Jun

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

Works citing "Predicting the Reasons of Customer Complaints: A First Step Toward Anticipating Quality Issues of In Vitro Diagnostics Assays with Machine Learning"