Swarnkar S. Artificial Intelligence Revolutionizing Cancer Care 2025

Textbook in PDF format

Preface
Editors
List of contributors
K-means clustering for knowledge discovery in big data cancer research
Applying reinforcement learning to optimize cancer treatment protocols in machine learning frameworks
Extraction of real-time data of breast cancer patients and implementation with ML techniques
Decoding images convolutional neural networks in oncological medical imaging
Uncovering insights in cancer research with centroid-based clustering on big data
The role of machine learning in remote cancer management: A systematic review
Revolutionizing cancer drug discovery deep learning neural networks for accelerated development
Empowering patients enhancing engagement and self-care in cancer treatment with Bayesian networks
Enhancing cancer detection and classification with ensemble machine learning approaches
Ethics, regulation, and machine learning navigating oncological AI deployment with decision trees
A comprehensive review of big data integration and K-Means clustering in cancer research
Applications of generative adversarial networks (GANs) in healthcare
Performance analysis of stochastic gradient descent and adaptive moment estimation optimization algorithms for convolutional neural networks
Enhancing oncology with predictive analytics for cancer diagnosis and treatment with random forests
Automated diagnosis of brain tumors from MRI scans using U-Net segmentation
Index