Assessing ChatGPT’s Educational Potential in Lung Cancer Radiotherapy From Clinician and Patient Perspectives: Content Quality and Readability Analysis
ChatGPT-4 shows promise as a supplementary tool for patient education in radiation oncology. While patients and clinicians appreciated the clarity and relevance of the information, limitations in completeness, trust, and readability highlight the need for clinician oversight and further optimization of LLM-generated content. Future developments should focus on improving accessibility, integrating real-time readability adaptation, and establishing standardized evaluation frameworks to ensure safe and effective clinical use.
Authors
- Stefanie Corradini (ORCID: https://orcid.org/0000-0001-8709-7252)
- Lukas Käsmann (ORCID: https://orcid.org/0000-0001-6260-5249)
- Mircea Gabriel Stoleriu (ORCID: https://orcid.org/0000-0002-1288-809X)
- Chukwuka Eze (ORCID: https://orcid.org/0000-0003-3779-1398)
- Claus Belka (ORCID: https://orcid.org/0000-0002-1287-7825)
- Nina-Sophie Schmidt-Hegemann (ORCID: https://orcid.org/0000-0002-2091-3603)
- Cedric Richlitzki
- Sina Mansoorian
- Thomas Duell (ORCID: https://orcid.org/0000-0002-1039-2090)
- Wulf Sienel
- Julia Kovács (ORCID: https://orcid.org/0009-0005-1952-399X)
- Diego Kauffmann‐Guerrero (ORCID: https://orcid.org/0000-0003-1471-3290)
Institutions
- German Cancer Research Center (DE)
- Heidelberg University (DE)
- LMU Klinikum (DE)
- Asklepios Fachkliniken München-Gauting (DE)
- German Center for Lung Research (DE)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- JMIR Cancer
- Published
- 2025-04-29
- DOI
- https://doi.org/10.2196/69783
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65