Being diagnosed with a rhabdomyosarcoma in the era of artificial intelligence: whom can we trust?
Open accessAbstract
In the era of big data, young patients may be overwhelmed by artificial intelligence‐based tools, like chatbots. Five clinical experts were asked to evaluate the performance of the most currently used chatbots in providing information on a rare cancer affecting young people, like rhabdomyosarcoma. Generally speaking, despite their high performance in giving general information about the disease, these chatbots were considered by the experts to be inadequate in providing suggestions on cancer treatments and specialized centers, and also lacking in “sensitivity.” Efforts are planned by the pediatric oncology community to improve the quality of data used to train these tools.
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Recent studies demonstrated that generative AI tools tailor educational content based on patient demographics, clinical context, and informational needs, including evaluations of ChatGPT and other LLMs responding to cancer-related questions and decision-making scenarios.
“Recent studies further extend this work by demonstrating how generative AI tools tailor educational content based on patient demographics, clinical context, and informational needs, including evaluations of ChatGPT and other large language models (LLMs) responding to cancer-related questions and decision-making scenarios [22-25].”
From Empathic AI for Patient-Centered Cancer Care: A Scoping Review of Patient Navigation, Support, and Clinical Practice (2026) · cites this paper as [23]
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Cited by
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White, B. M., Aitken, G. L., Zink, J. A., Kheirkhah Rahimabad, P., Kumsa, F. A., Hashtarkhani, S., Rashid, R., Kheirinejad, S., Girdwood, T., Brett, C. L., et al. (2026) · JMIR Cancer · doi:10.2196/82336 · Cited by 2 · see citing works
- Authors
- Clerici, C. A., Bernasconi, A., Lasalvia, P., Bisogno, G., Milano, G. M., Trama, A., Chiaravalli, S., Bergamaschi, L., Casanova, M., Massimino, M., & Ferrari, A.
- Affiliations
- University of Milan (IT)
- Fondazione IRCCS Istituto Nazionale dei Tumori (IT)
- University of Padua (IT)
- Bambino Gesù Children's Hospital (IT)
- Corresponding author
- Bernasconi, Alice
- ORCID
- Venue
- Pediatric Blood & Cancer
- Publisher
- Wiley
- Published
- 2024-08-11
- Volume
- 71
- Issue
- 11
- Pages
- e31256-e31256
- ISSN
- 1545-5009 (ISSN-L)
- 1545-5017
- OpenAlex
- W4401498919
- Cited by
- 8
- References
- 2
- Citations by year
- 2026: 5 · 2025: 3
- FWCI
- 0.75
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Pediatric Blood & Cancer (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Padua Research Archive (University of Padova) (submittedVersion, cc-by-nc-nd)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Health Professions › General Health Professions › Health Literacy and Information Accessibility
- Physical Sciences › Computer Science › Artificial Intelligence › AI in Service Interactions
- Keywords
- rhabdomyosarcoma, chatbots, artificial intelligence, information quality, cancer treatment recommendations, pediatric oncology, training data quality
- MeSH terms
- Artificial Intelligence, Child, Female, Humans, Rhabdomyosarcoma
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