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Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform
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....
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10487627/ https://www.ncbi.nlm.nih.gov/pubmed/37685452 http://dx.doi.org/10.3390/healthcare11172417 |
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author | Chow, James C. L. Wong, Valerie Sanders, Leslie Li, Kay |
author_facet | Chow, James C. L. Wong, Valerie Sanders, Leslie Li, Kay |
author_sort | Chow, James C. L. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-10487627 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104876272023-09-09 Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform Chow, James C. L. Wong, Valerie Sanders, Leslie Li, Kay Healthcare (Basel) Article 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. MDPI 2023-08-29 /pmc/articles/PMC10487627/ /pubmed/37685452 http://dx.doi.org/10.3390/healthcare11172417 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Chow, James C. L. Wong, Valerie Sanders, Leslie Li, Kay Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform |
title | Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform |
title_full | Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform |
title_fullStr | Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform |
title_full_unstemmed | Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform |
title_short | Developing an AI-Assisted Educational Chatbot for Radiotherapy Using the IBM Watson Assistant Platform |
title_sort | developing an ai-assisted educational chatbot for radiotherapy using the ibm watson assistant platform |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10487627/ https://www.ncbi.nlm.nih.gov/pubmed/37685452 http://dx.doi.org/10.3390/healthcare11172417 |
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