نبذة مختصرة : Healthcare is being transformed by AI-driven visualization, which transforms complex data into useful insights. This paper synthesizes advancements in AI visualization tools—spanning medical imaging, electronic health records (EHR), genomics, and public health—and evaluates their impact on diagnostics, treatment personalization, and operational efficiency. Convolutional neural networks (CNNs) for image segmentation, generative adversarial networks (GANs) for the generation of synthetic data, and interactive dashboards for real-time analytics are some of the technologies that we highlight. Integrity barriers, algorithmic bias, and data privacy concerns are all critically examined. A systematic review of more than 120 studies conducted between 2018 and 2024 shows that clinical workflow time is cut by 30% and diagnostic accuracy is improved by 40% on average. Explainable artificial intelligence (XAI) and federated learning are emphasized in the study's ethical frameworks and future directions. This study demonstrates that AI visualization plays a crucial role in value-based care and precision medicine.
Processing Request
No Comments.