Artificial Intelligence in Cancer Control Actions: Solution or Problem?
DOI:
https://doi.org/10.32635/2176-9745.RBC.2025v71n3.5291Keywords:
Artificial Intelligence, Preventive Medicine, Ethical TheoryAbstract
Artificial Intelligence (AI) has sparked significant attention in healthcare as it promises to speed up diagnoses, customize treatments and expand access. Machine learning and deep learning-based tools have already shown the ability to identify complex molecular patterns in oncology, foresee recurrence risks and help therapeutic decisions. However, despite its disruptive potential, the adoption of AI in cancer control actions raises ethical, technical and regulatory issues. Within this scenario, it is necessary to reflect critically: is AI a solution or a new challenge to prevent and control cancer?
Downloads
References
Aziz M, Ejaz SA, Zargar S, et al. Deep learning and structure-based virtual screening for drug discovery against NEK7: a novel target for the treatment of cancer. Molecules. 2022;27(13):4098. doi: https://doi.org/10.3390/molecules27134098 DOI: https://doi.org/10.3390/molecules27134098
Butt SR, Soulat A, Lal PM, et al. Impact of artificial intelligence on the diagnosis, treatment and prognosis of endometrial cancer. Ann Med Surg (Lond). 2024;86(3):1531-9. doi: https://doi.org/10.1097/ms9.0000000000001733 DOI: https://doi.org/10.1097/MS9.0000000000001733
Chen M, Copley SJ, Viola P, et al. Radiomics and artificial intelligence for precision medicine in lung cancer treatment. Semin Cancer Biol. 2023;93:97-113. doi: https://doi.org/10.1016/j.semcancer.2023.05.004 DOI: https://doi.org/10.1016/j.semcancer.2023.05.004
Kinikoglu O, Isik D. Evaluating the performance of ChatGPT-4o oncology expert in comparison to standard medical oncology knowledge: a focus on treatment-related clinical questions. Cureus. 2025;17(1):e78076. doi: https://doi.org/10.7759/cureus.78076 DOI: https://doi.org/10.7759/cureus.78076
Ebner F, Hartkopf A, Veselinovic K, et al. A comparison of ChatGPT and multidisciplinary team meeting treatment recommendations in 10 consecutive cervical cancer patients. Cureus. 2024;16(8):e67458. doi: https://doi.org/10.7759/cureus.67458 DOI: https://doi.org/10.7759/cureus.67458
Kim MS, Park HY, Kho BG, et al. Artificial intelligence and lung cancer treatment decision: agreement with recommendation of multidisciplinary tumor board. Transl Lung Cancer Res. 2020;9(3):507-14. doi: https://doi.org/10.21037/tlcr.2020.04.11 DOI: https://doi.org/10.21037/tlcr.2020.04.11
Liu C, Liu X, Wu F, et al. Using artificial intelligence (watson for oncology) for treatment recommendations amongst chinese patients with lung cancer: feasibility study. J Med Internet Res. 2018;20(9):e11087. doi: https://doi.org/10.2196/11087 DOI: https://doi.org/10.2196/11087
Bongurala AR, Save D, Virmani A. Progressive role of artificial intelligence in treatment decision-making in the field of medical oncology. Front Med (Lausanne). 2025;12:1533910. doi: https://doi.org/10.3389/fmed.2025.1533910 DOI: https://doi.org/10.3389/fmed.2025.1533910
Keshavarz P, Nezami N, Yazdanpanah F, et al. Prediction of treatment response and outcome of transarterial chemoembolization in patients with hepatocellular carcinoma using artificial intelligence: a systematic review of efficacy. Eur J Radiol. 2025;184:111948. doi: https://doi.org/10.1016/j.ejrad.2025.111948 DOI: https://doi.org/10.1016/j.ejrad.2025.112031
Published
How to Cite
Issue
Section
License
Os direitos morais e intelectuais dos artigos pertencem aos respectivos autores, que concedem à RBC o direito de publicação.

This work is licensed under a Creative Commons Attribution 4.0 International License.