Latest AI and machine learning research in transplantation for healthcare professionals.
Multi-modal retrieval-augmented generation (MRAG) systems retrieve visual evidence from large image ...
Cardiotoxicity remains a major cause of drug attrition and post-market withdrawal, yet the vast majo...
Metabolic dysfunction is increasingly recognized as a risk factor for poor outcomes in breast cancer...
Background: Inappropriate normalization can lead to data leakage and overfitting in machine learning...
Genome-wide association studies (GWAS) have cataloged thousands of disease-associated variants, yet ...
Reconstructing physically plausible 3D human-scene interactions (HSI) from a single image currently ...
Autoregressive video diffusion is emerging as a promising paradigm for streaming video synthesis, wi...
Background Randomized controlled trials (RCTs) often have incomplete methods reporting despite wides...
The translation of artificial intelligence into clinical practice depends, in large part, on access ...
The human brain varies across anatomical regions, cell types, development, ageing and disease states...
Generative Lung Architecture Modeling (GLAM) is an integrated bioengineering framework that couples ...
The function of a protein is intrinsically linked to its three-dimensional fold, and deep learning h...
Lung transplantation programs must decide when bilateral lung transplantation (BLT) offers meaningfu...
Engineering small-molecule binding proteins de novo remains a significant challenge as even advanced...
Proton therapy offers superior organ-at-risk sparing but is highly sensitive to anatomical changes, ...
Computational phantoms are widely used in medical imaging research, yet current systems to generate ...
Perturbation-based explainability methods such as KernelSHAP provide model-agnostic attributions but...
The interaction between T cell receptors (TCRs), peptides, and human leukocyte antigens (HLAs) under...
Generative models can now propose thousands of \emph{de novo} antibody sequences, yet translating th...
Cell state diversity drives tissue adaptability, repair, and disease resilience, but fully capturing...
Deep learning has been widely applied to 3D medical image segmentation tasks. However, due to the di...