The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a
wave of opportunities in computational healthcare. The interactive nature of these models …

Recent advancements in the field of medical artificial intelligence (AI) have led to the
widespread adoption of foundational and large language models. This review paper …

Deep learning has significantly advanced medical image processing, yet the inherent
inclusion of personally identifiable information (PII) within medical images—such as facial …

Diagnostic radiologists need artificial intelligence (AI) for medical imaging, but access to
medical images required for training in AI has become increasingly restrictive. To release …

In the realm of medical image analysis, self-supervised learning (SSL) techniques have
emerged to alleviate labeling demands, while still facing the challenge of training data …

In the realm of cardiovascular medicine, medical imaging plays a crucial role in accurately
classifying cardiac diseases and making precise diagnoses. However, the field faces …

To release medical images that can be freely used in downstream processes while
maintaining their utility, it is necessary to remove personal features from the images while …

In the realm of medical image analysis, self-supervised learning techniques (SSL) have
emerged to alleviate labeling demands, while still facing the challenge of training data …