Latest AI and machine learning research in transplantation for healthcare professionals.
Outfit generation is a challenging task in the field of fashion technology, in which the aim is to...
Acute kidney injury (AKI) is a frequent, severe complication of hematopoietic stem cell transplantat...
Cancer of unknown primary (CUP) constitutes between 2% and 5% of human malignancies and is among the...
The rapid integration of the Internet of Things (IoT) and Internet of Medical (IoM) devices in the...
Bluetooth Low Energy (BLE) location trackers, or "tags", are popular consumer devices for monitori...
The rapid evolution of cyber threats has outpaced traditional detection methodologies, necessitati...
Recent advancements in 3D content generation from text or a single image struggle with limited hig...
We define what it means for a joint probability distribution to be compatible with a set of indepe...
We introduce Baichuan-Omni-1.5, an omni-modal model that not only has omni-modal understanding cap...
Spiking Neural Networks (SNNs) hold promise for energy-efficient, biologically inspired computing....
Purpose: To automate contrast phase classification in CT using organ-specific features extracted f...
Annotating 3D medical images demands substantial time and expertise, driving the adoption of semi-...
The interconnection between the human lungs and other organs, such as the liver and kidneys, is cr...
Multi-organ segmentation is a critical yet challenging task due to complex anatomical backgrounds,...
Modern cybersecurity landscapes increasingly demand sophisticated detection frameworks capable of ...
Radiotherapy (RT) planning is complex, subjective, and time-intensive. Advances with artificial in...
Current self-supervised learning methods for 3D medical imaging rely on simple pretext formulation...
Despite coronary artery calcium scoring being considered a largely solved problem within the realm...
Infrared-visible image fusion (IVIF) is a critical task in computer vision, aimed at integrating t...
Recent advancements in language-guided diffusion models for image editing are often bottle-necked ...
Unsupervised representation learning has significantly advanced various machine learning tasks. In...