KEY TAKEAWAYS
- The study aimed to examine the latest technologies transforming tumor treatment and outcomes.
- The results revealed that federated learning and data consortiums can create safer, more powerful, and effective AI platforms.
Artificial intelligence (AI) is increasingly integrated into clinical practice within neurosurgical oncology, particularly for brain cancer. This technology is enhancing diagnostic accuracy and treatment planning.
Clayton R. Baker and the team aimed to explore the latest technologies revolutionizing tumor treatment and improving patient outcomes.
A research librarian assisted in conducting a rigorous literature search to identify key articles on AI and related topics, such as machine learning, computer vision, augmented reality, and virtual reality, in the neurosurgical care of brain and spinal tumors.
The results revealed that advances in AI, including machine learning, computer vision, and augmented/virtual reality, are improving the treatment of central nervous system (CNS) tumors. AI-aided diagnostic and prognostic tools can enhance the pre-operative patient experience, while automated tumor segmentation and total resection predictions aid in surgical planning.
Novel intra-operative tools quickly provide histopathologic tumor classification to streamline treatment strategies. Additionally, post-operative video analysis combined with detailed surgical simulations can improve training feedback and regimens.
The study concluded that despite concerns about limited generalizability, bias, and patient data security, federated learning and expanding data consortiums offer a pathway toward safer, more powerful, and effective AI platforms in the future.
No funding was provided.
Source: https://link.springer.com/article/10.1007/s11060-024-04757-5
Baker, C.R., Pease, M., Sexton, D.P. et al. (2024). “Artificial intelligence innovations in neurosurgical oncology: a narrative review.” J Neurooncol (2024). https://doi.org/10.1007/s11060-024-04757-5
