Radiology Today, Imaging Informatics: Breaking Down Siloes

The article "Imaging Informatics: Breaking Down Siloes" by Dr. Ittai Dayan, published in Radiology Today, discusses the transformative potential of federated learning in radiology. Federated learning is a machine learning technique that enables the training of models across multiple decentralized devices or servers without transferring data to a centralized location. This approach allows models to be trained locally on individual devices, with updates shared across the network, thereby preserving patient data privacy and security. Dr. Dayan highlights that, despite radiology's leadership in AI adoption, challenges remain in integrating numerous AI solutions into workflows and achieving expected outcomes. Federated learning offers a solution by facilitating collaborations without the need for data sharing between institutions, potentially leading to a significant scale-up of radiology data utilization and the development of more effective AI solutions in healthcare.