Latest AI and machine learning research in care of terminally ill / palliative care for healthcare professionals.
We are entering a new era of composite model architectures that integrate diverse components such as...
Spinal pathology is a leading cause of pain and disability worldwide. Spine MRI is central to clinic...
Extracting building polygon contours from high-resolution remote sensing images is a fundamental tas...
This paper introduces EPS3D, a new end-to-end feed-forward framework for open-vocabulary 3D panoptic...
Clinical artificial intelligence (AI) systems routinely produce predictions without principled quant...
End-to-end co-optimization of optical front-ends (e.g. metasurfaces) and neural network back-ends ha...
Embodied world models have emerged as a pivotal paradigm for visual robotic decision-making and inte...
Autonomous Underwater Vehicles (AUVs) traditionally rely on complex, heavily engineered pipelines fo...
Hyperspectral imaging provides rich spectral information for quantitative remote sensing, yet hypers...
Cell-type extraction is an important task in biomedical text mining because biomedical literature co...
Protein structure prediction via AlphaFold2 has revolutionized drug discovery, yet its end-to-end ex...
Neuroimaging based pain decoding faces two underappreciated challenges: between subject variability ...
The problem of object pose and shape estimation has seen key advancements lately. Encoder-decoder (e...
While the expansion of spatial omics has revolutionized our ability to dissect tissue architecture, ...
Objective: Survival analysis is central to medical prediction, yet large language models (LLMs) are ...
Real-world image restoration is challenging due to complex and interacting mixed degradations. Recen...
While large language models provide strong compositional reasoning, existing reasoning segmentation ...
Membrane transport is a fundamental biological process with profound implications for pharmacology, ...
Translating transcriptomic data into therapeutic hypotheses remains fragmented and labor-intensive. ...
Three-dimensional (3D) whole-organ imaging and analysis at cellular resolution (termed 3D histology)...
RGB-to-hyperspectral image reconstruction is a highly ill-posed inverse problem, since multiple plau...