“AI-ASSISTED RENAL TUMOR MANAGEMENT: A COMPARATIVE EVALUATION OF CHATGPT AND MULTIDISCIPLINARY TEAM DECISIONS”
Keywords:
Keywords: Artificial Intelligence, ChatGPT, Renal Tumors, Nephrectomy, Multidisciplinary Team, Decision-Making.Abstract
Abstract
Background:
Renal tumors, including renal cell carcinoma (RCC), often require complex and personalized decision-making processes, typically achieved through multidisciplinary team (MDT) discussions. With advancements in artificial intelligence (AI), tools like ChatGPT have the potential to aid decision-making. This study evaluates ChatGPT’s ability to align its recommendations with MDT decisions in renal tumor management.
Methods:
This retrospective study analyzed 13 renal tumor cases discussed by MDTs. Tumor classifications were based on the TNM staging system, including T1a, T1b, T2, T3/T4, and metastatic RCC. Treatment recommendations—partial nephrectomy, radical nephrectomy, systemic therapy, and surveillance—were generated by ChatGPT using the European Association of Urology (EAU) guidelines. Concordance with MDT decisions was assessed.
Results:
Localized RCC (T1-T2) accounted for 61.5% of cases, advanced RCC (T3/T4) for 15.4%, and metastatic RCC for 23.1%. Treatment recommendations included partial nephrectomy (23.1%), radical nephrectomy (46.2%), systemic therapy (23.1%), and surveillance (7.7%). ChatGPT demonstrated 100% concordance with MDT decisions across all cases.
Conclusion:
ChatGPT’s ability to align with MDT decisions underscores its potential as a supplementary tool in renal tumor management. However, human oversight is essential to account for patient-specific and contextual factors. Larger studies are required to validate these findings and refine AI integration into clinical workflows.
References
References:
1. Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70(1):7-30. doi:10.3322/caac.21590
2. Ray PP. ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things: Cyber-Physical Systems. 2023;6:100075. doi:10.1016/j.iotcps.2023.04.003
3. Strunga, M., Urban, R., Surovková, J., & Thurzo, A. (2023). Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment. Healthcare (Basel, Switzerland), 11(5), 683. https://doi.org/10.3390/healthcare11050683
4. Yeo YH, Samaan JS, Ng WH, et al. Assessing the performance of ChatGPT in answering questions regarding cirrhosis and hepatocellular carcinoma. Clin Mol Hepatol. 2023;29(4):594-604. doi:10.3350/cmh.2023.0089
5. Lecler A, Duron L, Soyer P. Revolutionizing radiology with GPT-based models: Current applications, future possibilities and limitations of ChatGPT. Diagn Interv Imaging. 2023;104(4):211-219. doi:10.1016/j.diii.2023.02.003
6. Liu J, Wang C, Liu S. Utility of ChatGPT in clinical practice. J Med Internet Res. 2023;25:e48568. doi:10.2196/48568
7. Gilson A, Safranek CW, Huang T, et al. How does ChatGPT perform on the United States Medical Licensing Examination (USMLE)? The implications of large language models for medical education and knowledge assessment. JMIR Med Educ. 2023;9:e47860. doi:10.2196/47860
8. Jeblick K, Schachtner B, Dexl J, et al. ChatGPT makes medicine easy to swallow: An exploratory case study on simplified radiology reports. Eur Radiol. 2023;33(5):2771-2777. doi:10.1007/s00330-023-09172-6
9. Escudier B, Porta C, Schmidinger M, et al. Renal cell carcinoma: ESMO Clinical Practice Guidelines for diagnosis, treatment, and follow-up. Ann Oncol. 2021;32(4):389-400. doi:10.1016/j.annonc.2021.01.015
10. European Association of Urology. Staging and Classification Systems. In: Renal Cell Carcinoma: EAU Guidelines. European Association of Urology; 2023. Available from: https://uroweb.org/guidelines/renal-cell-carcinoma/chapter/staging-and-classification-systems
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