Distributed Federated Learning-Based Deep Learning Model for Privacy MRI Brain Tumor Detection

arXiv:2404.10026v1 Announce Type: cross
Abstract: Distributed training can facilitate the processing of large medical image datasets, and improve the accuracy and efficiency of disease diagnosis while protecting patient privacy, which is crucial for achieving efficient medical image analysis and accelerating medical research progress. This paper presents an innovative approach to medical image classification, leveraging Federated Learning (FL) to address the dual challenges of data privacy and efficient disease diagnosis. Traditional Centralized Machine Learning models, despite their widespread use in medical …

accuracy analysis arxiv brain can cs.cr cs.lg datasets deep learning detection diagnosis disease distributed eess.iv efficiency federated federated learning image image analysis large medical medical research patient privacy privacy progress protecting research training