What is Federated learning?
Also: Federatif öğrenme
Federated learning, distributed model training without centralizing data. (Also: Federated learning.)
In terms of data and intelligence
Federated learning is concerned with applications that analyze clinical and operational data to provide input to teams and managers in decision-making processes.
How does it work?
In addition to model performance, data quality, explainability, and regulatory compliance are also part of success.
In summary
In short, federated learning is one of the building blocks that constitute the digital maturity of a healthcare institution; it is an approach that generates value when properly structured, rather than a singular tool.
For more in-depth information, you can refer to the AI-Supported Hospital Management page, and for related concepts, check the Digital Dictionary page.
Sık Sorulan Sorular
What is federated learning?
Distributed model training without centralizing data. (Also known as federated learning)
How is federated learning used in AI-supported processes?
Federated learning plays a role in transforming clinical and operational data into insights; it does not make decisions but supports the decisions of relevant teams.
Under which category is federated learning evaluated?
Federated learning is addressed under the Artificial Intelligence category in the context of health information systems and digital transformation.