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

Physician and Health Services Rating by Consumers (126) Telehealth and Telemonitoring (1566) Clinical Communication, Electronic Consultation and Telehealth (549) Quality Improvement (224) mHealth for Telemedicine and Homecare (364)

Published on in Vol 20, No 7 (2018): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9300, first published .
Evaluating Doctor Performance: Ordinal Regression-Based Approach

Evaluating Doctor Performance: Ordinal Regression-Based Approach

Evaluating Doctor Performance: Ordinal Regression-Based Approach

Authors of this article:

Yong Shi1, 2, 3, 4 Author Orcid Image ;   Peijia Li5, 6 Author Orcid Image ;   Xiaodan Yu7 Author Orcid Image ;   Huadong Wang2, 3 Author Orcid Image ;   Lingfeng Niu1, 2, 3 Author Orcid Image
Article Authors Cited by (4) Tweetations (11) Metrics

Journals

  1. Shi Y, Li P, Yuan H, Miao J, Niu L. Fast kernel extreme learning machine for ordinal regression. Knowledge-Based Systems 2019;177:44 View
  2. Pan W, Han Y, Li J, Zhang E, He B. The positive energy of netizens: development and application of fine-grained sentiment lexicon and emotional intensity model. Current Psychology 2023;42(32):27901 View

Books/Policy Documents

  1. Shi Y. Advances in Big Data Analytics. View