We are increasingly striving to introduce modern artificial intelligence techniques in medicine and elevate medical care, catering to both patients and specialists. An essential aspect that warrants concurrent development is the protection of personal data, especially with technology's advancement, along with addressing data disparities to ensure model efficacy. This study assesses various domain adaptation techniques and federated learning to determine optimal integration strategies for enhanced security and the challenges posed by diverse datasets. Experiments utilized deep learning models, three domain adaptation methods, and a federated learning framework, focusing on mammography imaging for breast cancer detection. Results indicate a notable improvement of up to 20% with domain adaptation and an additional 10% with federated learning integration.
Authors
Additional information
- DOI
- Digital Object Identifier link open in new tab 10.1109/hsi61632.2024.10613534
- Category
- Aktywność konferencyjna
- Type
- publikacja w wydawnictwie zbiorowym recenzowanym (także w materiałach konferencyjnych)
- Language
- angielski
- Publication year
- 2024
