ABSTRACT The advent of Artificial Intelligence (AI) in healthcare has marked a new era of
medical diagnostics and treatment. Particularly in the field of medical imaging, Deep …

Medical image analysis using deep neural networks (DNN) has demonstrated state-of-the-
art performance in image classification and segmentation tasks, aiding disease diagnosis …

Accepted: 12 January 2022 Deep Neural networks algorithms are recently used to solve
problems in medical imaging like no time ever. However, one of the main challenges for …

Medical image analysis is crucial for the efficient diagnosis of many diseases. Typically,
hospitals maintain vast repositories of images, which can be leveraged for various purposes …

Driven by the Deep Learning (DL) revolution, Artificial intelligence (AI) has become a
fundamental tool for many Bio-Medical tasks, including AI-assisted diagnosis. These include …

With the advent of the Internet of Things (IoT), artificial intelligence (AI), machine learning
(ML), and deep learning (DL) algorithms, the landscape of data-driven medical applications …

This thesis explores the application of Federated Learning (FL) in healthcare and medical
imaging, addressing the key challenge of utilizing large, dispersed medical datasets while …

Artificial intelligence (AI) holds great promise in healthcare as it can significantly advances
disease diagnosis using diverse medical datasets. However, learning generalizable …

Federated learning is an emerging research paradigm for enabling collaboratively training
deep learning models without sharing patient data. However, the data from different …

Machine learning and deep learning have demonstrated significant promise for many kinds
of medical imaging applications, including segmentation, classification, and detection. The …