Latest AI and machine learning research in transplantation for healthcare professionals.
Deep learning-based Organ-at-Risk (OAR) and tumor segmentation is vital for radiation therapy planning but often suffers from over-parameterization, requiring large datasets to avoid overfitting, which is impractical in small-sample medical settings. Traditional trainable parameter reduction methods, relying on structural lightweighting or low-rank approximation, may artificially limit model expre...
Streak artifacts in non-contrast computed tomography (NCCT) can obscure anatomical details and even confuse radiologic signs. Existing methods for artifact reduction have limitations: specialized training data and high annotation costs hinder the performance scalability, inadequate anatomical constraints struggle to preserve fine details, and limited generative stability along with suboptimal arti...
To realize practical quantum computers, a large number of quantum bits (qubits) will be required. Semiconductor spin qubits offer advantages such as h...
BACKGROUND: Delayed graft function (DGF) is a major complication of kidney transplantation that adversely affects long-term graft survival. This study...
Glioblastoma (GBM) is an aggressive brain tumor with highly variable patient outcomes due to pronounced molecular heterogeneity. Prognosis remains dis...
BACKGROUND: Combined liver transplantation (LT) and cardiac surgery (LT+CS) is a therapeutic option for patients with end-stage liver disease (ESLD) a...
INTRODUCTION/BACKGROUND: Segmentation of gastrointestinal (GI) organs-at-risk (OARs) is a critical yet time-consuming step in MR-guided adaptive radio...
Phosgene and acyl chlorides are highly toxic chemicals that pose serious threats to human health and environmental safety, yet their rapid and reliabl...
Molecular fluorophore dimerization has recently emerged as a powerful and versatile design strategy in phototheranostics, offering a distinct regulato...
Type 1 diabetes (T1D) is a T cell-mediated disease with a strong immunogenetic human leukocyte antigen (HLA) dependence. HLA allelic influence on the ...
BACKGROUND: Heart failure mortality has risen sharply after years of decline, highlighting the limitations of current risk assessment tools in accurac...
Ulcerative colitis (UC) represents a chronic, relapsing inflammatory condition primarily affecting the colonic and rectal mucosa, presenting substanti...
Out-of-distribution (OOD) detection has emerged as a crucial safeguard for ensuring trustworthy deployment of machine learning models in safety-critic...
BACKGROUND: This study aimed to assess the value of blood plasma autofluorescence spectroscopy in classifying renal injury after renal transplantation...
The advancement of robotic fish necessitates examination of whether caudal fins should be specifically designed for individual body shapes or if gener...
Neuromorphic Computing (NC) is a promising candidate for Artificial Intelligence (AI) applications. To realize NC, electronic analogues of brain compo...
BACKGROUND: The COVID-19 pandemic offers a powerful opportunity to develop methods for monitoring the spread of infectious diseases based on their sig...
Optimizing organic photovoltaic (OPV) performance requires navigating the high-dimensional, interdependent processing parameters governing bulk hetero...
The genetic mechanisms of ~90% of Alzheimer's disease (AD)-associated variants residing in noncoding DNA remain poorly understood. To address this, we...
RATIONALE AND OBJECTIVES: Accurate staging of hepatic fibrosis is essential for guiding immunosuppressive and antifibrotic therapies. However, percuta...