Continual and wisdom learning for federated learning: A comprehensive framework for robustness and debiasing DOI
Saeed Iqbal, Xiaopin Zhong, Muhammad Attique Khan

et al.

Information Processing & Management, Journal Year: 2025, Volume and Issue: 62(5), P. 104157 - 104157

Published: April 9, 2025

Language: Английский

Review of Federated Learning and Machine Learning-Based Methods for Medical Image Analysis DOI Creative Commons
Netzahualcoyotl Hernandez-Cruz,

Pramit Saha,

Md. Mostafa Kamal Sarker

et al.

Big Data and Cognitive Computing, Journal Year: 2024, Volume and Issue: 8(9), P. 99 - 99

Published: Aug. 28, 2024

Federated learning is an emerging technology that enables the decentralised training of machine learning-based methods for medical image analysis across multiple sites while ensuring privacy. This review paper thoroughly examines federated research applied to analysis, outlining technical contributions. We followed guidelines Okali and Schabram, a methodology, produce comprehensive summary discussion literature in information systems. Searches were conducted at leading indexing platforms: PubMed, IEEE Xplore, Scopus, ACM, Web Science. found total 433 papers selected 118 them further examination. The findings highlighted on applying neural network cardiology, dermatology, gastroenterology, neurology, oncology, respiratory medicine, urology. main challenges reported ability models adapt effectively real-world datasets privacy preservation. outlined two strategies address these challenges: non-independent identically distributed data privacy-enhancing methods. offers reference overview those already working field introduction new topic.

Language: Английский

Citations

7
PKMT-Net: A pathological knowledge-inspired multi-scale transformer network for subtype prediction of lung cancer using histopathological images DOI

Zhilei Zhao,

Shuli Guo,

Lina Han

et al.

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 106, P. 107742 - 107742

Published: Feb. 21, 2025

Language: Английский

Citations

0
Data-efficient federated semi-supervised learning framework via pseudo supervision refinement strategy for lung tumor segmentation DOI
Weixing Li,

Xipeng Pan,

Zhen Zhang

et al.

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 107, P. 107793 - 107793

Published: March 15, 2025

Language: Английский

Citations

0
Continual and wisdom learning for federated learning: A comprehensive framework for robustness and debiasing DOI
Saeed Iqbal, Xiaopin Zhong, Muhammad Attique Khan

et al.

Information Processing & Management, Journal Year: 2025, Volume and Issue: 62(5), P. 104157 - 104157

Published: April 9, 2025

Language: Английский

Citations

0