Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 43,131 to 43,140 of 223,853 articles

Discovery of a Hematopoietic Manifold in scGPT Yields a Method for Extracting Performant Algorithms from Biological Foundation Model Internals

arXiv Mar 10, 2026
We report the discovery and extraction of a compact hematopoietic algorithm from the single-cell foundation model scGPT, to our knowledge the first biologically useful, competitive algorithm extracted from a foundation model via mechanistic interpret... read more 
Machine Learning q-bio.CB q-bio.GN

ID-LoRA: Identity-Driven Audio-Video Personalization with In-Context LoRA

arXiv Mar 10, 2026
Existing video personalization methods preserve visual likeness but treat video and audio separately. Without access to the visual scene, audio models cannot synchronize sounds with on-screen actions; and because classical voice-cloning models condit... read more 
Sound cs.CV cs.GR

Joint Imaging-ROI Representation Learning via Cross-View Contrastive Alignment for Brain Disorder Classification

arXiv Mar 10, 2026
Brain imaging classification is commonly approached from two perspectives: modeling the full image volume to capture global anatomical context, or constructing ROI-based graphs to encode localized and topological interactions. Although both represent... read more 
Computer Vision and Pattern Recognition cs.AI

Why Does It Look There? Structured Explanations for Image Classification

arXiv Mar 10, 2026
Deep learning models achieve remarkable predictive performance, yet their black-box nature limits transparency and trustworthiness. Although numerous explainable artificial intelligence (XAI) methods have been proposed, they primarily provide salienc... read more 
Computer Vision and Pattern Recognition cs.LG

OilSAM2: Memory-Augmented SAM2 for Scalable SAR Oil Spill Detection

arXiv Mar 10, 2026
Segmenting oil spills from Synthetic Aperture Radar (SAR) imagery remains challenging due to severe appearance variability, scale heterogeneity, and the absence of temporal continuity in real world monitoring scenarios. While foundation models such a... read more 
Computer Vision and Pattern Recognition

FusionNet: a frame interpolation network for 4D heart models

arXiv Mar 10, 2026
Cardiac magnetic resonance (CMR) imaging is widely used to visualise cardiac motion and diagnose heart disease. However, standard CMR imaging requires patients to lie still in a confined space inside a loud machine for 40-60 min, which increases pati... read more 
Computer Vision and Pattern Recognition cs.LG

Delta-K: Boosting Multi-Instance Generation via Cross-Attention Augmentation

arXiv Mar 10, 2026
While Diffusion Models excel in text-to-image synthesis, they often suffer from concept omission when synthesizing complex multi-instance scenes. Existing training-free methods attempt to resolve this by rescaling attention maps, which merely exacerb... read more 
Computer Vision and Pattern Recognition cs.AI

ARCHE: Autoregressive Residual Compression with Hyperprior and Excitation

arXiv Mar 10, 2026
Recent progress in learning-based image compression has demonstrated that end-to-end optimization can substantially outperform traditional codecs by jointly learning compact latent representations and probabilistic entropy models. However, many exist... read more 
Image and Video Processing cs.CV cs.LG

DT-BEHRT: Disease Trajectory-aware Transformer for Interpretable Patient Representation Learning

arXiv Mar 10, 2026
The growing adoption of electronic health record (EHR) systems has provided unprecedented opportunities for predictive modeling to guide clinical decision making. Structured EHRs contain longitudinal observations of patients across hospital visits, w... read more 
Machine Learning

Unbalanced Optimal Transport Dictionary Learning for Unsupervised Hyperspectral Image Clustering

arXiv Mar 10, 2026
Hyperspectral images capture vast amounts of high-dimensional spectral information about a scene, making labeling an intensive task that is resistant to out-of-the-box statistical methods. Unsupervised learning of clusters allows for automated segmen... read more 
Computer Vision and Pattern Recognition cs.LG math.ST
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