The Future Prospect of Integrating Machine Learning and Nanocarbon Materials in Cancer Treatment: A Prospective Review

Cancer, as one of the leading causes of global mortality, requires novel therapeutic approaches with high efficiency and low side effects. In this regard, combining artificial intelligence (AI), particularly machine learning (ML), with nanocarbon materials such as carbon nanotubes and graphene has brought new hope. Hence, this review aims to investigate the role of ML in optimizing diagnosis, predicting treatment response, and designing smart nanocarriers based on nanocarbon. Nanotechnology and AI enable targeted drug delivery, photothermal therapy, and more accurate imaging. For example, carbon nanoparticles can deliver chemotherapy drugs directly to tumors, while ML predictive models analyze medical images to accurately assess a patient’s response to treatment and recommend the best course of action. This convergence of technologies has opened up new hopes for the fight against cancer. However, there are challenges, such as the potential toxicity of nanocarbons, the need for extensive clinical data to train ML models, and integrating these technologies into therapeutic systems. In the future, the development of smarter nanocarriers, aided by machine learning and further studies on the biocompatibility of nanocarbons, could lead to more personalized and effective therapies. In conclusion, the integration of ML and nanocarbons has the potential to revolutionize oncology, but interdisciplinary research and large-scale clinical trials are necessary to achieve practical application.

کلیدواژه ها:

Artificial intelligence ، Cancer treatment ، Drug Delivery ، Machine Learning ، Nanocarbon ، Nanotechnology