Cited by 24Artificial Intelligence in Healthcare and EducationArtificial Intelligence in HealthcareAI in cancer detection

Exploring the role of ChatGPT in oncology: providing information and support for cancer patients

Open access
Cè, Maurizio, Chiarpenello, Vittoria, Bubba, Alessandra, Felisaz, Paolo Florent, Oliva, Giancarlo, Irmici, Giovanni, Cellina, Michaela·2024·BioMedInformatics

Abstract

Introduction: Oncological patients face numerous challenges throughout their cancer journey while navigating complex medical information. The advent of AI-based conversational models like ChatGPT (San Francisco, OpenAI) represents an innovation in oncological patient management. Methods: We conducted a comprehensive review of the literature on the use of ChatGPT in providing tailored information and support to patients with various types of cancer, including head and neck, liver, prostate, breast, lung, pancreas, colon, and cervical cancer. Results and Discussion: Our findings indicate that, in most instances, ChatGPT responses were accurate, dependable, and aligned with the expertise of oncology professionals, especially for certain subtypes of cancers like head and neck and prostate cancers. Furthermore, the system demonstrated a remarkable ability to comprehend patients’ emotional responses and offer proactive solutions and advice. Nevertheless, these models have also showed notable limitations and cannot serve as a substitute for the role of a physician under any circumstances. Conclusions: Conversational models like ChatGPT can significantly enhance the overall well-being and empowerment of oncological patients. Both patients and healthcare providers must become well-versed in the advantages and limitations of these emerging technologies.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/biomedinformatics4020049

Cites

8 of 8 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • AI technologies provide timely, accurate, and accessible information that can empower patients and caregivers, supporting engagement, comprehension, and autonomy throughout the cancer care continuum.

    “These technologies provide timely, accurate, and accessible information that can empower patients and caregivers, supporting engagement, comprehension, and autonomy throughout the cancer care continuum [6-8].”

    From Empathic AI for Patient-Centered Cancer Care: A Scoping Review of Patient Navigation, Support, and Clinical Practice (2026) · cites this paper as [6]

    Sections 3.1.2 and 3.1.3 describe ChatGPT as making information easier and faster to obtain and understand, including for patients and caregivers, with potential to improve participation and shared decision-making. The Conclusions say it can offer accurate, accessible support throughout patients’ cancer journey, but also warn that its information can be inaccurate or unreliable. The claim overstates accuracy as an unqualified property of AI technologies generally. (LLM, conf=0.82)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 36

  1. Pokorski, M., Ed.; Advances in Experimental Medicine and Biology; Springer International Publishing: Cham, Switzerland, 2019; Volume 1211, pp. 1-16. [CrossRef] · DOI
  2. Yeung, A.W.K.; Tosevska, A.; Klager, E.; Eibensteiner, F.; Tsagkaris, C.; Parvanov, E.D.; Nawaz, F.A.; Völkl-Kernstock, S.; Schaden, E.; Kletecka-Pulker, M.; et al. Medical and Health-Related Misinformation on Social Media: Bibliometric Study of the Scientific Literature. J. Med. Internet Res. 2022, 24, e28152. [CrossRef] [PubMed] · DOI
  3. Cancer Misinformation and Harmful Information on Facebook and Other Social Media: A Brief Report. Available online: https://pubmed.ncbi.nlm.nih.gov/34291289/ (accessed on 21 February 2024).
  4. Schäfer, W.L.A.; Van Den Berg, M.J.; Groenewegen, P.P. The Association between the Workload of General Practitioners and Patient Experiences with Care: Results of a Cross-Sectional Study in 33 Countries. Hum. Resour. Health 2020, 18, 76. [CrossRef] [PubMed] · DOI
  5. Dave, T.; Athaluri, S.A.; Singh, S. ChatGPT in Medicine: An Overview of Its Applications, Advantages, Limitations, Future Prospects, and Ethical Considerations. Front. Artif. Intell. 2023, 6, 1169595. [CrossRef] [PubMed] · DOI · Paper page
  6. Li, Y.; Gao, W.; Luan, Z.; Zhou, Z.; Li, J. The Impact of Chat Generative Pre-Trained Transformer (ChatGPT) on Oncology: Application, Expectations, and Future Prospects. Cureus 2023, 15, e48670. [CrossRef] [PubMed] · DOI · Paper page
  7. Chatterjee, J.; Dethlefs, N. This New Conversational AI Model Can Be Your Friend, Philosopher, and Guide . . . and Even Your Worst Enemy. Patterns 2023, 4, 100676. [CrossRef] [PubMed] · DOI · Paper page
  8. Hirosawa, T.; Harada, Y.; Yokose, M.; Sakamoto, T.; Kawamura, R.; Shimizu, T. Diagnostic Accuracy of Differential-Diagnosis Lists Generated by Generative Pretrained Transformer 3 Chatbot for Clinical Vignettes with Common Chief Complaints: A Pilot Study. Int. J. Environ. Res. Public Health 2023, 20, 3378. [CrossRef] [PubMed] · DOI
  9. Kung, T.H.; Cheatham, M.; Medenilla, A.; Sillos, C.; De Leon, L.; Elepaño, C.; Madriaga, M.; Aggabao, R.; Diaz-Candido, G.; Maningo, J.; et al. Performance of ChatGPT on USMLE: Potential for AI-Assisted Medical Education Using Large Language Models. PLoS Digit. Health 2023, 2, e0000198. [CrossRef] · DOI · Paper page
  10. DeWalt, D.A.; Berkman, N.D.; Sheridan, S.; Lohr, K.N.; Pignone, M.P. Literacy and Health Outcomes: A Systematic Review of the Literature. J. Gen. Intern. Med. 2004, 19, 1228-1239. [CrossRef] [PubMed] · DOI · Paper page
  11. Budhathoki, S.S.; Pokharel, P.K.; Good, S.; Limbu, S.; Bhattachan, M.; Osborne, R.H. The Potential of Health Literacy to Address the Health Related UN Sustainable Development Goal 3 (SDG3) in Nepal: A Rapid Review. BMC Health Serv. Res. 2017, 17, 237. [CrossRef] [PubMed] · DOI
  12. Perrone, F.; Jommi, C.; Di Maio, M.; Gimigliano, A.; Gridelli, C.; Pignata, S.; Ciardiello, F.; Nuzzo, F.; De Matteis, A.; Del Mastro, L.; et al. The Association of Financial Difficulties with Clinical Outcomes in Cancer Patients: Secondary Analysis of 16 Academic Prospective Clinical Trials Conducted in Italy. Ann. Oncol. 2016, 27, 2224-2229. [CrossRef] · DOI
  13. Zhu, L.; Mou, W.; Chen, R. Can the ChatGPT and Other Large Language Models with Internet-Connected Database Solve the Questions and Concerns of Patient with Prostate Cancer and Help Democratize Medical Knowledge? J. Transl. Med. 2023, 21, 269. [CrossRef] [PubMed] · DOI
  14. Rao, A.; Kim, J.; Kamineni, M.; Pang, M.; Lie, W.; Succi, M.D. Evaluating ChatGPT as an Adjunct for Radiologic Decision-Making. MedRxiv 2023. preprint. [CrossRef] · DOI · Paper page
  15. Campbell, D.J.; Estephan, L.E. ChatGPT for Patient Education: An Evolving investigation. J. Clin. Sleep Med. 2023, 19, 2135-2136. [CrossRef] [PubMed] · DOI
  16. Ryan, H.; Schofield, P.; Cockburn, J.; Butow, P.; Tattersall, M.; Turner, J.; Girgis, A.; Bandaranayake, D.; Bowman, D. How to Recognize and Manage Psychological Distress in Cancer Patients. Eur. J. Cancer Care 2005, 14, 7-15. [CrossRef] [PubMed] · DOI
  17. Dekker, J.; Graves, K.D.; Badger, T.A.; Diefenbach, M.A. Management of Distress in Patients with Cancer-Are We Doing the Right Thing? Ann. Behav. Med. 2020, 54, 978-984. [CrossRef] [PubMed] · DOI
  18. Dolan, N.C.; Ferreira, M.R.; Davis, T.C.; Fitzgibbon, M.L.; Rademaker, A.; Liu, D.; Schmitt, B.P.; Gorby, N.; Wolf, M.; Bennett, C.L. Colorectal Cancer Screening Knowledge, Attitudes, and Beliefs Among Veterans: Does Literacy Make a Difference? J. Clin. Oncol. 2004, 22, 2617-2622. [CrossRef] [PubMed] · DOI
  19. Zheng, Y.; Wu, Y.; Feng, B.; Wang, L.; Kang, K.; Zhao, A. Enhancing Diabetes Self-Management and Education: A Critical Analysis of ChatGPT's Role. Ann. Biomed. Eng. 2023, 52, 741-744. [CrossRef] [PubMed] · DOI
  20. Yeo, Y.H.; Samaan, J.S.; Ng, W.H.; Ting, P.-S.; Trivedi, H.; Vipani, A.; Ayoub, W.; Yang, J.D.; Liran, O.; Spiegel, B.; et al. Assessing the Performance of ChatGPT in Answering Questions Regarding Cirrhosis and Hepatocellular Carcinoma. Clin. Mol. Hepatol. 2023, 29, 721-732. [CrossRef] [PubMed] · DOI
  21. Yapar, D.; Demir Avcı, Y.; Tokur Sonuvar, E.; Faruk E gerci, Ö.; Yapar, A. ChatGPT's Potential to Support Home Care for Patients in the Early Period after Orthopedic Interventions and Enhance Public Health. Jt. Dis. Relat. Surg. 2024, 35, 169-176. [CrossRef] [PubMed] · DOI
  22. Borkowski, A.A. Applications of ChatGPT and Large Language Models in Medicine and Health Care: Benefits and Pitfalls. Fed. Pract. 2023, 40, 170. [CrossRef] · DOI
  23. Tsang, R. Practical Applications of ChatGPT in Undergraduate Medical Education. J. Med. Educ. Curric. Dev. 2023, 10, 238212052311784. [CrossRef] [PubMed] · DOI
  24. Khan, R.A.; Jawaid, M.; Khan, A.R.; Sajjad, M. ChatGPT-Reshaping Medical Education and Clinical Management. Pak. J. Med. Sci. 2023, 39. [CrossRef] [PubMed] · DOI · Paper page
  25. Kitamura, F.C. ChatGPT Is Shaping the Future of Medical Writing But Still Requires Human Judgment. Radiology 2023, 307, e230171. [CrossRef] [PubMed] · DOI · Paper page
  26. Kuşcu, O.; Pamuk, A.E.; Sütay Süslü, N.; Hosal, S. Is ChatGPT Accurate and Reliable in Answering Questions Regarding Head and Neck Cancer? Front. Oncol. 2023, 13, 1256459. [CrossRef] · DOI
  27. Wei, K.; Fritz, C.; Rajasekaran, K. Answering Head and Neck Cancer Questions: An Assessment of ChatGPT Responses. Am. J. Otolaryngol. 2024, 45, 104085. [CrossRef] · DOI
  28. Shaw, J.; Patidar, K.R.; Reuter, B.; Hajezifar, N.; Dharel, N.; Wade, J.B.; Bajaj, J.S. Focused Education Increases Hepatocellular Cancer Screening in Patients with Cirrhosis Regardless of Functional Health Literacy. Dig. Dis. Sci. 2021, 66, 2603-2609. [CrossRef] [PubMed] · DOI
  29. Liu, H.Y.; Alessandri Bonetti, M.; De Lorenzi, F.; Gimbel, M.L.; Nguyen, V.T.; Egro, F.M. Consulting the Digital Doctor: Google Versus ChatGPT as Sources of Information on Breast Implant-Associated Anaplastic Large Cell Lymphoma and Breast Implant Illness. Aesthetic Plast. Surg. 2023, 48, 590-607. [CrossRef] [PubMed] · DOI
  30. Rahsepar, A.A.; Tavakoli, N.; Kim, G.H.J.; Hassani, C.; Abtin, F.; Bedayat, A. How AI Responds to Common Lung Cancer Questions: ChatGPT versus Google Bard. Radiology 2023, 307, e230922. [CrossRef] [PubMed] · DOI
  31. Emile, S.H.; Horesh, N.; Freund, M.; Pellino, G.; Oliveira, L.; Wignakumar, A.; Wexner, S.D. How Appropriate Are Answers of Online Chat-Based Artificial Intelligence (ChatGPT) to Common Questions on Colon Cancer? Surgery 2023, 174, 1273-1275. [CrossRef] [PubMed] · DOI
  32. Moazzam, Z.; Cloyd, J.; Lima, H.A.; Pawlik, T.M. Quality of ChatGPT Responses to Questions Related to Pancreatic Cancer and Its Surgical Care. Ann. Surg. Oncol. 2023, 30, 6284-6286. [CrossRef] [PubMed] · DOI
  33. Hermann, C.E.; Patel, J.M.; Boyd, L.; Growdon, W.B.; Aviki, E.; Stasenko, M. Let's Chat about Cervical Cancer: Assessing the Accuracy of ChatGPT Responses to Cervical Cancer Questions. Gynecol. Oncol. 2023, 179, 164-168. [CrossRef] [PubMed] · DOI
  34. Nedbal, C.; Naik, N.; Castellani, D.; Gauhar, V.; Geraghty, R.; Somani, B.K. ChatGPT in Urology Practice: Revolutionizing Efficiency and Patient Care with Generative Artificial Intelligence. Curr. Opin. Urol. 2024, 34, 98-104. [CrossRef] [PubMed] · DOI
  35. Dahmen, J.; Kayaalp, M.E.; Ollivier, M.; Pareek, A.; Hirschmann, M.T.; Karlsson, J.; Winkler, P.W. Artificial Intelligence Bot ChatGPT in Medical Research: The Potential Game Changer as a Double-Edged Sword. Knee Surg. Sports Traumatol. Arthrosc. 2023, 31, 1187-1189. [CrossRef] [PubMed] · DOI · Paper page
  36. Whiles, B.B.; Bird, V.G.; Canales, B.K.; DiBianco, J.M.; Terry, R.S. Caution! AI Bot Has Entered the Patient Chat: ChatGPT Has Limitations in Providing Accurate Urologic Healthcare Advice. Urology 2023, 180, 278-284. [CrossRef · DOI · Paper page

Cited by

Sorted by citations

Authors
Cè, M., Chiarpenello, V., Bubba, A., Felisaz, P. F., Oliva, G., Irmici, G., & Cellina, M.
Affiliations
  • University of Milan (IT)
  • ASST Fatebenefratelli Sacco (IT)
  • Fondazione IRCCS Istituto Nazionale dei Tumori (IT)
Venue
BioMedInformatics
Publisher
MDPI AG
Published
2024-03-25
Volume
4
Issue
2
Pages
877-888
ISSN
2673-7426 (ISSN-L)
OpenAlex
W4393160742
Cited by
24
References
8
Citations by year
2026: 4 · 2025: 16 · 2024: 4
FWCI
2.27
Type
journal article
Language
en
Open access
Locations
  • BioMedInformatics (publishedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
  • Physical Sciences › Computer Science › Artificial Intelligence › AI in cancer detection
Keywords
ChatGPT, large language models, cancer patients, patient information, patient support, conversational AI, head and neck cancer, prostate cancer, breast cancer, lung cancer, colon cancer, cervical cancer, liver cancer, pancreatic cancer, emotional support, patient empowerment, AI limitations

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review