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

Digital Health Reviews (1318) Chatbots and Conversational Agents (542) Mobile Health (mhealth) (2974) Web-based and Mobile Health Interventions (3344) Telehealth and Telemonitoring (1710)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/41583, first published .
Developing a Technical-Oriented Taxonomy to Define Archetypes of Conversational Agents in Health Care: Literature Review and Cluster Analysis

Developing a Technical-Oriented Taxonomy to Define Archetypes of Conversational Agents in Health Care: Literature Review and Cluster Analysis

Developing a Technical-Oriented Taxonomy to Define Archetypes of Conversational Agents in Health Care: Literature Review and Cluster Analysis

Authors of this article:

Kerstin Denecke1 Author Orcid Image ;   Richard May2 Author Orcid Image
Article Authors Cited by (13) Tweetations (7) Metrics

Journals

  1. Denecke K. Framework for Guiding the Development of High-Quality Conversational Agents in Healthcare. Healthcare 2023;11(8):1061 View
  2. Denecke K. Potential and pitfalls of conversational agents in health care. Nature Reviews Disease Primers 2023;9(1) View
  3. Kiuchi K, Otsu K, Hayashi Y. Psychological insights into the research and practice of embodied conversational agents, chatbots and social assistive robots: a systematic meta-review. Behaviour & Information Technology 2024;43(15):3696 View
  4. Llanes-Jurado J, Gómez-Zaragozá L, Minissi M, Alcañiz M, Marín-Morales J. Developing conversational Virtual Humans for social emotion elicitation based on large language models. Expert Systems with Applications 2024;246:123261 View
  5. Laymouna M, Ma Y, Lessard D, Schuster T, Engler K, Lebouché B. Roles, Users, Benefits, and Limitations of Chatbots in Health Care: Rapid Review. Journal of Medical Internet Research 2024;26:e56930 View
  6. Sezgin E, Kocaballi A, Dolce M, Skeens M, Militello L, Huang Y, Stevens J, Kemper A. Chatbot for Social Need Screening and Resource Sharing With Vulnerable Families: Iterative Design and Evaluation Study. JMIR Human Factors 2024;11:e57114 View
  7. Denecke K, Reichenpfader D, Willi D, Kennel K, Bonel H, Nairz K, Cihoric N, Papaux D, von Tengg-Kobligk H. Person-based design and evaluation of MIA, a digital medical interview assistant for radiology. Frontiers in Artificial Intelligence 2024;7 View
  8. Babushkina D, de Boer B. Disrupted self, therapy, and the limits of conversational AI. Philosophical Psychology 2024:1 View
  9. Baumgärtner K, Byczkowski M, Schmid T, Muschko M, Woessner P, Gerlach A, Bonekamp D, Schlemmer H, Hohenfellner M, Görtz M. Effectiveness of the Medical Chatbot PROSCA to Inform Patients About Prostate Cancer: Results of a Randomized Controlled Trial. European Urology Open Science 2024;69:80 View
  10. Heumann M, Kraschewski T, Werth O, Breitner M. Reassessing taxonomy-based data clustering: Unveiling insights and guidelines for application. Decision Support Systems 2024;187:114344 View

Books/Policy Documents

  1. Visakh P, Meena P, Anoop V. Multi-disciplinary Trends in Artificial Intelligence. View