Recent advances in deep learning (DL) have shown that data-driven insights can be used in
smart healthcare applications to improve the quality of life for patients. DL needs more data …

A disease is an abnormal condition that negatively impacts the functioning of the human
body. Pathology determines the causes behind the disease and identifies its development …

The use of machine learning (ML) with electronic health records (EHR) is growing in
popularity as a means to extract knowledge that can improve the decision-making process in …

Availability of large amount of annotated data is one of the pillars of deep learning success.
Although numerous big datasets have been made available for research, this is often not the …

Abstract Machine learning has revolutionized every facet of human life, while also becoming
more accessible and ubiquitous. Its prevalence has had a powerful impact in healthcare …

Due to the fast advancement of artificial intelligence (AI), centralized-based models have
become critical for healthcare tasks like in medical image analysis and human behavior …

Federated Learning (FL) obtained a lot of attention to the academic and industrial
stakeholders from the beginning of its invention. The eye-catching feature of FL is handling …

Medical images are private integrations comprising private patient information owned by
various hospitals and relevant research institutes, and the generated image data can be …

Data plays a vital role in deep learning model training. In large-scale medical image
analysis, data privacy and ownership make data gathering challenging in a centralized …

Federated learning (FL) has emerged with increasing popularity in the medical image
analysis field. In collaborative model training, it provides a privacy-preserving scheme by …