As patients are divided into ever more narrowly defined subgroups, the number of individuals available for research shrinks dramatically. While this approach improves personalization, it also creates ...

AI medical imaging market is projected to exceed $20B by 2035. Generative models address class imbalances in medical imaging ...

In an era where data breaches make headlines weekly and privacy regulations tighten globally, artificial intelligence faces a fundamental challenge: how to learn from data without compromising privacy ...

A collaborative approach to training AI models can yield better results, but it requires finding partners with data that complements your own. José Parra-Moyano, Karl Schmedders, and Maximilian Werner ...

Brain tumors account for roughly one in four cancer-related deaths. The task of brain tumor segmentation is particularly challenging, as different tumor types require distinct segmentation approaches.

With the growing demand for data privacy protection, traditional centralized machine learning methods have gradually exposed their limitations in the face of data privacy risks. In many practical ...

Abstract: In this paper, we study the decentralized federated learning problem, which involves the collaborative training of a global model among multiple devices while ensuring data privacy. In ...

Each year, cyberattacks become more frequent and data breaches become more expensive. Whether companies seek to protect their AI system during development or use their algorithm to improve their ...

The reliance on public data — mostly web data — to train AI is holding back the AI field. That’s according to Daniel Beutel, a tech entrepreneur and researcher at the University of Cambridge, who ...

Jiaming Xu, an associate professor at Duke’s Fuqua School of Business says federated learning is a new approach that holds the promise of transforming Artificial Intelligence (AI) systems training. Xu ...