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

Natural Language Processing (553) Clinical Information and Decision Making (1112) Machine Learning (1189)

Published on in Vol 5, No 3 (2017): Jul-Sept

Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers

Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers

Triaging Patient Complaints: Monte Carlo Cross-Validation of Six Machine Learning Classifiers

Authors of this article:

Adel Elmessiry 1 Author Orcid Image ;   William O Cooper 2 Author Orcid Image ;   Thomas F Catron 2 Author Orcid Image ;   Jan Karrass 2 Author Orcid Image ;   Zhe Zhang 3 Author Orcid Image ;   Munindar P Singh 1 Author Orcid Image
Article Authors Cited by (8) Tweetations (8) Metrics

Journals

  1. Spasic I, Nenadic G. Clinical Text Data in Machine Learning: Systematic Review. JMIR Medical Informatics 2020;8(3):e17984 View
  2. van Dael J, Reader T, Gillespie A, Neves A, Darzi A, Mayer E. Learning from complaints in healthcare: a realist review of academic literature, policy evidence and front-line insights. BMJ Quality & Safety 2020;29(8):684 View
  3. Liu Y, Wan Y, Su X. Identifying individual expectations in service recovery through natural language processing and machine learning. Expert Systems with Applications 2019;131:288 View
  4. Anagnostou P, Tasoulis S, Vrahatis A, Georgakopoulos S, Prina M, Ayuso-Mateos J, Bickenbach J, Bayes-Marin I, Caballero F, Egea-Cortés L, García-Esquinas E, Leonardi M, Scherbov S, Tamosiunas A, Galas A, Haro J, Sanchez-Niubo A, Plagianakos V, Panagiotakos D. Enhancing the Human Health Status Prediction: The ATHLOS Project. Applied Artificial Intelligence 2021;35(11):834 View

Books/Policy Documents

  1. Xia C, Zhao D, Wang J, Liu J, Ma J. Smart Health. View
  2. Galitsky B. Artificial Intelligence for Healthcare Applications and Management. View