Leveraging Artificial Intelligence to Bolster Equitable Cancer Care

In a conversation with CancerNetwork^®, Viviana Cortiana, MS4, and Yan Leyfman, MD, spoke about their manuscript titled “Artificial Intelligence in Cancer Care: Addressing Challenges and Health Equity,” which they published in the April 2025 issue of ONCOLOGY^®.

Cortiana is a medical student in the Department of Medical and Surgical Sciences at the University of Bologna. Leyfman is a resident physician from the Icahn School of Medicine of the Mount Sinai Health System.

Cortiana highlighted how artificial intelligence (AI)–based tools may mitigate the overdiagnosis of cancers, although she noted a need to validate these devices with diverse and high-quality datasets to avoid the risk of biased models. Additionally, she described how developing population-specific AI models may improve predictive accuracy in diagnosis as well as treatment planning, which can especially benefit patients in low- and middle-income countries.

As part of ethically applying the use of AI to oncology and delivering equitable cancer care, Leyfman emphasized core pillars such as data security, transparency, clinical validation, and combatting algorithmic bias. Furthermore, he stated that potential applications of these tools include mobile diagnostics, cloud-based platforms, and remote consultation, which can help increase access to care. Regarding the potential next steps in the field, he highlighted that global partnerships with parties such as tech companies, governments, and non-governmental organizations may assist with the funding and deployment of AI tools, especially for underserved regions.

“The future of AI in oncology is increasingly promising, not just in pushing the boundaries of what's possible in cancer care but also making sure that more precise and more accessible worldwide therapies are available,” Leyfman stated. “AI has the potential to fundamentally change how we detect, treat, and monitor [cancer], but realizing that promise, especially in a way that's equitable, will require collaboration, validation, thoughtful implementation, and a commitment to leaving no patient behind.”