In the past decade, the application of machine learning (ML) to healthcare has helped drive
the automation of physician tasks as well as enhancements in clinical capabilities and …

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 BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the
Radiological Society of North America (RSNA), the American Society of Neuroradiology …

Medical artificial intelligence (AI) has tremendous potential to advance healthcare by
supporting and contributing to the evidence-based practice of medicine, personalizing …

Federated Learning (FL) is a novel approach enabling several clients holding sensitive data
to collaboratively train machine learning models, without centralizing data. The cross-silo FL …

In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark
(LiTS), which was organized in conjunction with the IEEE International Symposium on …

Objective. Federated learning (FL) is a computational paradigm that enables organizations
to collaborate on machine learning (ML) and deep learning (DL) projects without sharing …

Glioblastoma is the most common aggressive adult brain tumor. Numerous studies have
reported results from either private institutional data or publicly available datasets. However …

Trustworthy artificial intelligence (TAI) has proven invaluable in curbing potential negative
repercussions tied to AI applications. Within the TAI spectrum, federated learning (FL) …

Artificial intelligence (AI) shows potential to improve health care by leveraging data to build
models that can inform clinical workflows. However, access to large quantities of diverse …