This paper presents a comprehensive systematic review of generative models (GANs, VAEs,
DMs, and LLMs) used to synthesize various medical data types, including imaging …

Image synthesis is increasingly being adopted in medical image processing, for example for
data augmentation or inter-modality image translation. In these critical applications, the …

Purpose: To determine whether the retinal nerve fiber layer thickness can be used as an
indicator for systemic neurodegeneration in diabetes. Methods: We used existing data from …

Large medical datasets are crucial for advancing contemporary medical practices that
incorporate computer vision and machine learning techniques. These records serve as …

Graph Neural Networks (GNNs) have gained significant attention in recent years. They
compromise a flexible and powerful deep learning concept for multimodal graph-structured …

Since the late 17th century, unprecedented magnification has provided insights into the
previously unknown world of microorganisms. This development led to the development of …