Latest AI and machine learning research in transplantation for healthcare professionals.
Personalized outfit generation aims to construct a set of compatible and personalized fashion items as an outfit. Recently, generative AI models have received widespread attention, as they can generate fashion items for users to complete an incomplete outfit or create a complete outfit. However, they have limitations in terms of lacking diversity and relying on the supervised learning paradigm. ...
In radiation therapy planning, inaccurate segmentations of organs at risk can result in suboptimal treatment delivery, if left undetected by the clinician. To address this challenge, we developed a denoising autoencoder-based method to detect inaccurate organ segmentations. We applied noise to ground truth organ segmentations, and the autoencoders were tasked to denoise them. Through the applica...
Diffusion Probabilistic Models (DPMs) have demonstrated significant potential in 3D medical image segmentation tasks. However, their high computatio...
Multi-modal large language models (MLLMs) have made significant progress, yet their safety alignment remains limited. Typically, current open-source...
The segmentation of multiple organs in multi-parametric MRI studies is critical for many applications in radiology, such as correlating imaging biom...
Reliable localization is critical for robot navigation in complex indoor environments. In this paper, we propose an uncertainty-aware localization m...
Large language models (LLMs) have increasingly been used to extract critical information from unstructured clinical notes, which often include importa...
Instance segmentation plays a pivotal role in medical image analysis by enabling precise localization and delineation of lesions, tumors, and anatom...
We examine the performance of an Integrated Access and Backhaul (IAB) node as a range extender for beyond-5G networks, focusing on the significant c...
LLMs have gained immense popularity among researchers and the general public for its impressive capabilities on a variety of tasks. Notably, the eff...
The increasing adoption of UAVs with advanced sensors and GPU-accelerated edge computing has enabled real-time AI-driven applications in fields such...
Diffusion models are widely used for image editing tasks. Existing editing methods often design a representation manipulation procedure by curating ...
Despite the impressive performance across a wide range of applications, current computational pathology models face significant diagnostic efficienc...
In recent years, deep learning methods such as convolutional neural network (CNN) and transformers have made significant progress in CT multi-organ ...
Background: The HERMES Kiosk (Healthcare Enhanced Recommendations through Artificial Intelligence & Expertise System) is designed to provide persona...
Complex cell signaling systems -- governed by varying protein abundances and interactions -- generate diverse cell types across organs. These system...
Recent advances in general medical AI have made significant strides, but existing models often lack the reasoning capabilities needed for complex me...
High-fidelity garment modeling remains challenging due to the lack of large-scale, high-quality datasets and efficient representations capable of ha...
The Artificial Intelligence models pose serious challenges in intensive computing and high-bandwidth communication for conventional electronic circu...
The rising demand for energy-efficient edge AI systems (e.g., mobile agents/robots) has increased the interest in neuromorphic computing, since it o...