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

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9960, first published .
Predicting the Reasons of Customer Complaints: A First Step Toward Anticipating Quality Issues of In Vitro Diagnostics Assays with Machine Learning

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

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

Authors of this article:

Stephane Aris-Brosou1 Author Orcid Image ;   James Kim2 Author Orcid Image ;   Li Li2 Author Orcid Image ;   Hui Liu2 Author Orcid Image

Journals

  1. 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 View
  2. Long G, Hussen M, Dench J, Aris-Brosou S. Identifying genetic determinants of complex phenotypes from whole genome sequence data. BMC Genomics 2019;20(1) View
  3. 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 View
  4. Rani S, Kumar R, Panda B, Kumar R, Muften N, Abass M, Lozanović J. Machine Learning-Powered Smart Healthcare Systems in the Era of Big Data: Applications, Diagnostic Insights, Challenges, and Ethical Implications. Diagnostics 2025;15(15):1914 View

Conference Proceedings

  1. Ansari A, Schlueter N, Heinrichsmeyer M, Loewer M. 2020 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). Development and Validation of a Failure-Cause-Searching and Solution-Finding Algorithm Based on Complaint Information from the Use Phase View
  2. Gewaly M, Saeed M, Ammar A. 2024 Intelligent Methods, Systems, and Applications (IMSA). Machine Learning Approach for Complaint Prediction in the Telecom Industry View