Revolutionizing cancer surgery: Harnessing artificial intelligence and augmented reality for next-generation precision oncology
1 Department of Supply Chain Management, Marketing, and Management, Wright State University, Ohio, USA.
2 Department of Internal Medicine (Consulting group), Obafemi Awolowo University Health Center, Ile-Ife, Nigeria.
3 Department of Mathematics and Statistics (Data Science) Dept. / American University Washington DC.
4 Department of Electrical and Computer Engineering, Tennessee Technological University, Tennessee, United States.
5 Department of Medicine, College of Health Sciences, Obafemi Awolowo University, Ile-Ife, Nigeria.
6 Department of Molecular Biology and Biotechnology, Nigerian institute of Medical research, Yaba, Nigeria.
7 Department of General Medicine, Yangtze University, Jingzhou City, China.
Review
International Journal of Life Science Research Archive, 2025, 09(01), 147–176.
Article DOI: 10.53771/ijlsra.2025.9.1.0051
Publication history:
Received on 21 July 2025; revised on 06 September 2025; accepted on 08 September 2025
Abstract:
In the rapidly evolving landscape of precision oncology, the convergence of artificial intelligence (AI) and augmented reality (AR) is redefining cancer surgery with unparalleled accuracy and transformative potential. This review synthesizes a robust body of clinical evidence, drawn from over 80 peer-reviewed studies, to illuminate how AI’s sophisticated data analytics and AR’s immersive visualization synergize to enhance every phase of oncologic intervention—from preoperative tumor characterization to intraoperative navigation and postoperative monitoring. AI-driven algorithms excel in decoding complex imaging and genomic data, enabling precise tumor staging and risk stratification, while AR overlays provide real-time, dynamic guidance for resecting tumors in challenging anatomical regions like the brain, liver, and lungs. Integrated AI-AR systems, particularly in robotic-assisted procedures, have demonstrated remarkable reductions in operative time, blood loss, and positive margin rates, alongside improved survival and quality-of-life outcomes in cancers such as breast, lung, and kidney. Yet, challenges like data bias, algorithmic transparency, and equitable access, particularly in resource-limited settings, underscore the need for innovative solutions like extended reality and open-source platforms. This manuscript charts a visionary path forward, advocating for collaborative research and policy reforms to democratize these technologies, ensuring that the promise of precision oncology—where every incision is informed by data-driven insight and visual clarity—becomes a global reality, revolutionizing cancer care with precision, equity, and hope.
Keywords:
Artificial Intelligence; Augmented Reality; Precision Oncology; Cancer Surgery; Robotic Surgery; Multimodal Imaging; Machine Learning; Tumor Visualization.
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Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0