School of Medicine Publications
Document Type
Article
Publication Date
7-29-2025
Abstract
Purpose: Cancer immunotherapy has transformed oncology, but underserved populations face persistent disparities in access and outcomes. This review explores how artificial intelligence (AI) can help mitigate these barriers. Methods: We conducted a narrative review based on peer-reviewed literature selected for relevance to artificial intelligence, cancer immunotherapy, and healthcare challenges, without restrictions on publication date. We searched three major electronic databases: PubMed, IEEE Xplore, and arXiv, covering both biomedical and computational literature. The search included publications from January 2015 through April 2024 to capture contemporary developments in AI and cancer immunotherapy. Results: AI tools such as machine learning, natural language processing, and predictive analytics can enhance early detection, personalize treatment, and improve clinical trial representation for historically underrepresented populations. Additionally, AI-driven solutions can aid in managing side effects, expanding telehealth, and addressing social determinants of health (SDOH). However, algorithmic bias, privacy concerns, and data diversity remain major challenges. Conclusions: With intentional design and implementation, AI holds the potential to reduce disparities in cancer immunotherapy and promote more inclusive oncology care. Future efforts must focus on ethical deployment, inclusive data collection, and interdisciplinary collaboration.
Recommended Citation
Vasquez, V. M., Jr, McCabe, M., McKee, J. C., Siby, S., Hussain, U., Faizuddin, F., Sheikh, A., Nguyen, T., Mayer, G., Grier, J., Dhandayuthapani, S., Gadad, S. S., & Chacon, J. (2025). Transforming Cancer Care: A Narrative Review on Leveraging Artificial Intelligence to Advance Immunotherapy in Underserved Communities. Journal of clinical medicine, 14(15), 5346. https://doi.org/10.3390/jcm14155346
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication Title
Journal of clinical medicine
DOI
10.3390/jcm14155346
Academic Level
faculty
Mentor/PI Department
Medical Education
Comments
© 2025 by the authors.
Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).