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

Background To develop deep learning models for medical diagnosis, it is important to collect
more medical data from several medical institutions. Due to the regulations for privacy …

Deep learning-based medical image analysis is an effective and precise method for
identifying various cancer types. However, due to concerns over patient privacy, sharing …

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 …

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 …

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

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

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 …

Data-driven models often require a large amount of data for sufficient training. Federated
learning (FL) is a machine learning framework that can effectively help multiple sites utilize …

Lung cancer is a leading contributor to cancer-related fatalities worldwide, and
histopathological image analysis plays a critical role in cancer detection by identifying …