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Cited by 60Artificial Intelligence in Healthcare and EducationAI in Service InteractionsSpeech and dialogue systems

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform

Open access
Chow, James C. L., Wong, Valerie, Sanders, Leslie, Li, Kay·2023·Healthcare
DOI 10.3390/healthcare11172417PMC PMC10487627
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Abstract

Objectives: This study aims to make radiotherapy knowledge regarding healthcare accessible to the general public by developing an AI-powered chatbot. The interactive nature of the chatbot is expected to facilitate better understanding of information on radiotherapy through communication with users. Methods: Using the IBM Watson Assistant platform on IBM Cloud, the chatbot was constructed following a pre-designed flowchart that outlines the conversation flow. This approach ensured the development of the chatbot with a clear mindset and allowed for effective tracking of the conversation. The chatbot is equipped to furnish users with information and quizzes on radiotherapy to assess their understanding of the subject. Results: By adopting a question-and-answer approach, the chatbot can engage in human-like communication with users seeking information about radiotherapy. As some users may feel anxious and struggle to articulate their queries, the chatbot is designed to be user-friendly and reassuring, providing a list of questions for the user to choose from. Feedback on the chatbot’s content was mostly positive, despite a few limitations. The chatbot performed well and successfully conveyed knowledge as intended. Conclusions: There is a need to enhance the chatbot’s conversation approach to improve user interaction. Including translation capabilities to cater to individuals with different first languages would also be advantageous. Lastly, the newly launched ChatGPT could potentially be developed into a medical chatbot to facilitate knowledge transfer.

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Crossref · 10.3390/healthcare11172417

Cites

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Figures

Figure 1 Flowchart of chatbot dialogue.
Figure 1 Flowchart of chatbot dialogue.CC BY · PubMed Central
Figure 2 Page showing the list of actions created using the IBM Watson API.
Figure 2 Page showing the list of actions created using the IBM Watson API.CC BY · PubMed Central
Figure 3 Application programing interfaces showing the training of the chatbot with possible phases.
Figure 3 Application programing interfaces showing the training of the chatbot with possible phases.CC BY · PubMed Central
Figure 4 Demonstrations of the RT Bot (a) continuing to provide similar therapy information, (b) responding to the user who requires additional information after completing a section, and (c) saying farewell to the user.
Figure 4 Demonstrations of the RT Bot (a) continuing to provide similar therapy information, (b) responding to the user who requires additional information after completing a section, and (c) saying farewell to the user.CC BY · PubMed Central
Figure 5 Demonstration of (a) ceasing receiving information on the same type of therapy and (b) triggering the fallback action.
Figure 5 Demonstration of (a) ceasing receiving information on the same type of therapy and (b) triggering the fallback action.CC BY · PubMed Central

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Citations

Cites

Research works printed but not linked: 3

  1. Chow, J.C. (2021). Artificial Intelligence in Medicine, Springer International Publishing.
  2. Augello, A., Gentile, M., Weideveld, L., and Dignum, F. (2016). Intelligent Interactive Multimedia Systems and Services 2016, Springer.
  3. Clarizia, F., Colace, F., Lombardi, M., Pascale, F., and Santaniello, D. (2018). International Symposium on Cyberspace Safety and Security 2018, Springer.

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Metadata

Authors
Chow, J. C. L., Wong, V., Sanders, L., & Li, K.
Affiliations
  • University Health Network (CA)
  • Toronto Metropolitan University (CA)
  • York University (CA)
  • University of Toronto (CA)
Corresponding author
Chow, James C. L.
ORCID
Venue
Healthcare
Publisher
MDPI AG
Published
2023-08-29
Volume
11
Issue
17
Pages
2417
ISSN
2227-9032 (ISSN-L)
DOI
10.3390/healthcare11172417
PMC
PMC10487627
OpenAlex
W4386256552
Cited by
60
References
37
Citations by year
2026: 9 · 2025: 20 · 2024: 29 · 2023: 2
FWCI
2.39
Type
journal article
Language
en
Open access
Licence
Locations
  • Healthcare (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • TSpace (University of Toronto) (submittedVersion, cc-by)
Funders
Canadian Institutes of Health Research Planning and Dissemination Grant—Institute Community Support (CIHR PCS–168296)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
Keywords
radiotherapy, educational chatbots, conversational AI, public health education, patient information, user interaction, ChatGPT, multilingual translation

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