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

Information Retrieval (294) Peer-to-Peer Support and Online Communities (646) Information Seeking, Information Needs (478)

Published on in Vol 19, No 12 (2017): December

Automatic Classification of Users’ Health Information Need Context: Logistic Regression Analysis of Mouse-Click and Eye-Tracker Data

Automatic Classification of Users’ Health Information Need Context: Logistic Regression Analysis of Mouse-Click and Eye-Tracker Data

Automatic Classification of Users’ Health Information Need Context: Logistic Regression Analysis of Mouse-Click and Eye-Tracker Data

Authors of this article:

Wenjing Pian1 Author Orcid Image ;   Christopher SG Khoo2 Author Orcid Image ;   Jianxing Chi3 Author Orcid Image
Article Authors Cited by (9) Tweetations (7) Metrics

Journals

  1. Gwizdka J, Zhang Y, Dillon A. Using the eye-tracking method to study consumer online health information search behaviour. Aslib Journal of Information Management 2019;71(6):739 View
  2. Lv H, Yang X, Wang B, Wang S, Du X, Tan Q, Hao Z, Liu Y, Yan J, Xia Y. Machine Learning–Driven Models to Predict Prognostic Outcomes in Patients Hospitalized With Heart Failure Using Electronic Health Records: Retrospective Study. Journal of Medical Internet Research 2021;23(4):e24996 View
  3. Klaib A, Alsrehin N, Melhem W, Bashtawi H, Magableh A. Eye tracking algorithms, techniques, tools, and applications with an emphasis on machine learning and Internet of Things technologies. Expert Systems with Applications 2021;166:114037 View
  4. Han Q. Topics and Trends of Health Informatics Education Research: Scientometric Analysis. JMIR Medical Education 2024;10:e58165 View

Books/Policy Documents

  1. Alfano M, Lenzitti B, Taibi D, Helfert M. Information and Communication Technologies for Ageing Well and e-Health. View
  2. Alfano M, Lenzitti B, Taibi D, Helfert M. Information and Communication Technologies for Ageing Well and e-Health. View