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 accessAbstract
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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“Additionally, with the rapid advancements in nursing research and the advent of new diseases and medications, nursing professionals are challenged to quickly adapt to evolving medical knowledge, make accurate decisions in real-case scenarios, and master complex nursing skills (1, 17, 26–28).”
From Digital affordances of AI chatbots in nursing education: a systematic review of learning gains and gaps in the evidence (2026) · cites this paper as [27]
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ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education
Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · doi:10.35542/osf.io/5er8f · Cited by 7,552
ChatGPT for good? On opportunities and challenges of large language models for education
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., et al. (2023) · Learning and Individual Differences · doi:10.1016/j.lindif.2023.102274 · Cited by 7,326 · cited 1×
“OpenAI recently launched a generative language model tool called ChatGPT, which uses a new type of AI algorithm known as LLM [40].”
MethodLiu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2023) · ACM Computing Surveys · doi:10.1145/3560815 · Cited by 4,361 · cited 1×
“In addition, the chatbot built on the IBM Watson Assistant platform is AI-assisted and utilizes machine learning capabilities such as NLP [29–31].”
MethodLiu, P., Yuan, W., Fu, J., Jiang, Z., Hayashi, H., & Neubig, G. (2021) · arXiv · doi:10.48550/arxiv.2107.13586 · Cited by 4,352 · cited 1×
“In addition, the chatbot built on the IBM Watson Assistant platform is AI-assisted and utilizes machine learning capabilities such as NLP [29–31].”
MethodCancer and Radiation Therapy: Current Advances and Future Directions
Baskar, R., Lee, K. A., Yeo, R., & Yeoh, K. (2012) · International Journal of Medical Sciences · doi:10.7150/ijms.3635 · Cited by 2,927
Natural language processing: an introduction
Nadkarni, P. M., Lucila Ohno-machado, A., & Chapman, W. W. (2011) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2011-000464 · Cited by 2,127
Advances in natural language processing
Hirschberg, J., & Manning, C. D. (2015) · Science · doi:10.1126/science.aaa8685 · Cited by 1,712
Rapp, A., Curti, L., & Boldi, A. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102630 · Cited by 733
Estimating the demand for radiotherapy from the evidence: A review of changes from 2003 to 2012
Barton, M. B., Jacob, S., Shafiq, J., Wong, K. K. Y., Thompson, S. R., Hanna, T. P., & Delaney, G. P. (2014) · Radiotherapy and Oncology · doi:10.1016/j.radonc.2014.03.024 · Cited by 542
Should Machines Express Sympathy and Empathy? Experiments with a Health Advice Chatbot
Liu, B., & Sundar, S. S. (2018) · Cyberpsychology, Behavior, and Social Networking · doi:10.1089/cyber.2018.0110 · Cited by 447
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Research works printed but not linked: 3
- Chow, J.C. (2021). Artificial Intelligence in Medicine, Springer International Publishing.
- Augello, A., Gentile, M., Weideveld, L., and Dignum, F. (2016). Intelligent Interactive Multimedia Systems and Services 2016, Springer.
- 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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Industrial applications of large language models
Raza, M., Jahangir, Z., Riaz, M. B., Saeed, M. J., & Sattar, M. A. (2025) · Scientific Reports · doi:10.1038/s41598-025-98483-1 · Cited by 247
Quantum Computing and Machine Learning in Medical Decision-Making: A Comprehensive Review
Chow, J. C. L. (2025) · Algorithms · doi:10.3390/a18030156 · Cited by 122
Chow, J. C. L., Wong, V., & Li, K. (2024) · BioMedInformatics · doi:10.3390/biomedinformatics4010047 · Cited by 101
Chow, J. C. L., & Li, K. (2025) · Information · doi:10.3390/info16070549 · Cited by 84
Self-citationThe Potential Applications and Challenges of ChatGPT in the Medical Field
Mu, Y., & He, D. (2024) · International Journal of General Medicine · doi:10.2147/ijgm.s456659 · Cited by 84
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.
- Venue
- Healthcare
- Publisher
- MDPI AG
- Published
- 2023-08-29
- Volume
- 11
- Issue
- 17
- Pages
- 2417
- ISSN
- 2227-9032 (ISSN-L)
- 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
- gold
- doi.org
- 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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