Latest AI and machine learning research in transplantation for healthcare professionals.
Multi-organ biological aging is often represented as parallel organ-specific clocks, but how age gap...
Background: Per- and polyfluoroalkyl substances (PFAS), particularly perfluorooctane sulfonate (PFOS...
Three-dimensional (3D) whole-organ imaging and analysis at cellular resolution (termed 3D histology)...
Annotating bounding boxes is costly and limits the scalability of object detection. This challenge i...
Effective anti-tumor T cell response depends on both neoantigen quality (non-selfness) and quantity ...
Foundation models (FMs) have shown great promise in medical imaging, but most FMs are trained on uni...
Recent studies have explored generating virtual spatial transcriptomics (ST) profiles from histologi...
We introduce a causal aware foundation-model framework for real time optimal decision making in disc...
Manually curated biomedical repositories -- spanning bioactivity, genomics, and chemistry -- are exp...
We introduce iTRIALSPACE, a programmable evaluation framework for controlled assessment of lung CT m...
Continual learning (CL) is essential for deploying medical image segmentation models in clinical env...
Background: People with Multiple Long-Term Conditions (MLTC) experience higher rates of organ failur...
Biomedical knowledge graphs have emerged as foundational infrastructure for AI-driven drug discovery...
Disease is a heterogeneous process that involves multiple organs and cell types. Understanding how g...
Organoids are complex, three dimensional, self-organizing cell cultures which manifest organ-like fe...
T-cell receptor (TCR) repertoires encode the organization of adaptive immunity and its reshaping by ...
Mobile remote identity verification (RIdV) systems are exposed to attacks that manipulate or replace...
Robotic ultrasound has advanced local image-driven control, contact regulation, and view optimizatio...
Identifying species in biology among tens of thousands of visually similar taxa while discovering un...
Chest computed tomography (CT) is central to the detection and management of thoracic disease, yet t...
Deep learning-based nuclei segmentation and classification in pathology images typically rely on lar...