AI Assistant in Brain Tumor Prediction: A Comprehensive Review of Techniques, Trends, and Future Prospects
Abstract: AI (Artificial Intelligence) is transforming medical imaging, especially regarding the early and precise identification of brain tumors like gliomas, meningiomas, and pituitary adenomas. AI (Artificial Intelligence) is transforming medical imaging, especially regarding the early and precise identification of brain tumors like gliomas, meningiomas, and pituitary adenomas. Special attention is given to convolutional neural networks (CNNs), which are commonly used due to their capability of capturing spatial and hierarchical features from MRI scans. Architectures like U-Net, ResNet, and DenseNet, as well as hybrid models, are examined for their efficacy in tumor classification and segmentation. Algorithm selection, clinical applicability, and dataset considerations are also discussed in the review. This paper delineates the changing function of AI assistants in brain tumor prediction and the prospective trajectory of AI-driven diagnostic processes in clinical environments by integrating contemporary trends and developments.
Keywords: AI Assistant, Brain Tumor Prediction, MRI, Deep, Deep Learning, CNN, Medical Imaging, Machine Learning, Healthcare AI
How to Cite?: Aparna Sharma, Saurav Kumar Jha, Rajesh Kumar, "AI Assistant in Brain Tumor Prediction: A Comprehensive Review of Techniques, Trends, and Future Prospects", Volume 14 Issue 5, May 2025, International Journal of Science and Research (IJSR), Pages: 1491-1504, https://www.ijsr.net/getabstract.php?paperid=SR25524225311, DOI: https://dx.doi.org/10.21275/SR25524225311