NYMC Faculty Publications
Artificial Intelligence Advancements in Oncology: A Review of Current Trends and Future Directions
Author Type(s)
Student, Faculty
DOI
10.3390/biomedicines13040951
Journal Title
Biomedicines
Document Type
Article
Publication Date
4-1-2025
Department
Pathology, Microbiology and Immunology
Second Department
Neurology
Keywords
artificial intelligence, cancer, deep learning, machine learning, nanomedicine, oncology, social determinants of health
Disciplines
Medicine and Health Sciences
Abstract
Cancer remains one of the leading causes of mortality worldwide, driving the need for innovative approaches in research and treatment. Artificial intelligence (AI) has emerged as a powerful tool in oncology, with the potential to revolutionize cancer diagnosis, treatment, and management. This paper reviews recent advancements in AI applications within cancer research, focusing on early detection through computer-aided diagnosis, personalized treatment strategies, and drug discovery. We survey AI-enhanced diagnostic applications and explore AI techniques such as deep learning, as well as the integration of AI with nanomedicine and immunotherapy for cancer care. Comparative analyses of AI-based models versus traditional diagnostic methods are presented, highlighting AI’s superior potential. Additionally, we discuss the importance of integrating social determinants of health to optimize cancer care. Despite these advancements, challenges such as data quality, algorithmic biases, and clinical validation remain, limiting widespread adoption. The review concludes with a discussion of the future directions of AI in oncology, emphasizing its potential to reshape cancer care by enhancing diagnosis, personalizing treatments and targeted therapies, and ultimately improving patient outcomes.
Recommended Citation
Huhulea, E., Huang, L., Eng, S., Sumawi, B., Huang, A., Aifuwa, E., Hirani, R., Tiwari, R., & Etienne, M. (2025). Artificial Intelligence Advancements in Oncology: A Review of Current Trends and Future Directions. Biomedicines, 13 (4). https://doi.org/10.3390/biomedicines13040951
