AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative Study
BackgroundStructured and standardized documentation is critical for accurately recording diagnostic findings, treatment plans, and patient progress in health care. Manual documentation can be labor-intensive and error-prone, especially under time constraints, prompting intere...
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| Format: | Article |
| Language: | English |
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JMIR Publications
2024-12-01
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| Series: | Journal of Medical Internet Research |
| Online Access: | https://www.jmir.org/2024/1/e60684 |
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| _version_ | 1846111131282702336 |
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| author | Daniel Stephan Annika Bertsch Matthias Burwinkel Shankeeth Vinayahalingam Bilal Al-Nawas Peer W Kämmerer Daniel GE Thiem |
| author_facet | Daniel Stephan Annika Bertsch Matthias Burwinkel Shankeeth Vinayahalingam Bilal Al-Nawas Peer W Kämmerer Daniel GE Thiem |
| author_sort | Daniel Stephan |
| collection | DOAJ |
| description |
BackgroundStructured and standardized documentation is critical for accurately recording diagnostic findings, treatment plans, and patient progress in health care. Manual documentation can be labor-intensive and error-prone, especially under time constraints, prompting interest in the potential of artificial intelligence (AI) to automate and optimize these processes, particularly in medical documentation.
ObjectiveThis study aimed to assess the effectiveness of ChatGPT (OpenAI) in generating radiology reports from dental panoramic radiographs, comparing the performance of AI-generated reports with those manually created by dental students.
MethodsA total of 100 dental students were tasked with analyzing panoramic radiographs and generating radiology reports manually or assisted by ChatGPT using a standardized prompt derived from a diagnostic checklist.
ResultsReports generated by ChatGPT showed a high degree of textual similarity to reference reports; however, they often lacked critical diagnostic information typically included in reports authored by students. Despite this, the AI-generated reports were consistent in being error-free and matched the readability of student-generated reports.
ConclusionsThe findings from this study suggest that ChatGPT has considerable potential for generating radiology reports, although it currently faces challenges in accuracy and reliability. This underscores the need for further refinement in the AI’s prompt design and the development of robust validation mechanisms to enhance its use in clinical settings. |
| format | Article |
| id | doaj-art-a7248f92b3d4413aab3a8a4d6512c791 |
| institution | Kabale University |
| issn | 1438-8871 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | Journal of Medical Internet Research |
| spelling | doaj-art-a7248f92b3d4413aab3a8a4d6512c7912024-12-23T13:01:14ZengJMIR PublicationsJournal of Medical Internet Research1438-88712024-12-0126e6068410.2196/60684AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative StudyDaniel Stephanhttps://orcid.org/0009-0007-2480-1231Annika Bertschhttps://orcid.org/0009-0000-4159-7745Matthias Burwinkelhttps://orcid.org/0009-0002-1780-4796Shankeeth Vinayahalingamhttps://orcid.org/0000-0002-2679-3841Bilal Al-Nawashttps://orcid.org/0000-0002-8665-5803Peer W Kämmererhttps://orcid.org/0000-0002-1671-3764Daniel GE Thiemhttps://orcid.org/0000-0002-4081-1487 BackgroundStructured and standardized documentation is critical for accurately recording diagnostic findings, treatment plans, and patient progress in health care. Manual documentation can be labor-intensive and error-prone, especially under time constraints, prompting interest in the potential of artificial intelligence (AI) to automate and optimize these processes, particularly in medical documentation. ObjectiveThis study aimed to assess the effectiveness of ChatGPT (OpenAI) in generating radiology reports from dental panoramic radiographs, comparing the performance of AI-generated reports with those manually created by dental students. MethodsA total of 100 dental students were tasked with analyzing panoramic radiographs and generating radiology reports manually or assisted by ChatGPT using a standardized prompt derived from a diagnostic checklist. ResultsReports generated by ChatGPT showed a high degree of textual similarity to reference reports; however, they often lacked critical diagnostic information typically included in reports authored by students. Despite this, the AI-generated reports were consistent in being error-free and matched the readability of student-generated reports. ConclusionsThe findings from this study suggest that ChatGPT has considerable potential for generating radiology reports, although it currently faces challenges in accuracy and reliability. This underscores the need for further refinement in the AI’s prompt design and the development of robust validation mechanisms to enhance its use in clinical settings.https://www.jmir.org/2024/1/e60684 |
| spellingShingle | Daniel Stephan Annika Bertsch Matthias Burwinkel Shankeeth Vinayahalingam Bilal Al-Nawas Peer W Kämmerer Daniel GE Thiem AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative Study Journal of Medical Internet Research |
| title | AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative Study |
| title_full | AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative Study |
| title_fullStr | AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative Study |
| title_full_unstemmed | AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative Study |
| title_short | AI in Dental Radiology—Improving the Efficiency of Reporting With ChatGPT: Comparative Study |
| title_sort | ai in dental radiology improving the efficiency of reporting with chatgpt comparative study |
| url | https://www.jmir.org/2024/1/e60684 |
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