Artificial Intelligence Medical Compendium

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

Showing 54,531 to 54,540 of 226,183 articles

Fully Kolmogorov-Arnold Deep Model in Medical Image Segmentation

arXiv Feb 3, 2026
Deeply stacked KANs are practically impossible due to high training difficulties and substantial memory requirements. Consequently, existing studies can only incorporate few KAN layers, hindering the comprehensive exploration of KANs. This study over... read more 
Computer Vision and Pattern Recognition cs.LG

BinaryDemoire: Moiré-Aware Binarization for Image Demoiréing

arXiv Feb 3, 2026
Image demoiréing aims to remove structured moiré artifacts in recaptured imagery, where degradations are highly frequency-dependent and vary across scales and directions. While recent deep networks achieve high-quality restoration, their full-precisi... read more 
Computer Vision and Pattern Recognition

Spectral Evolution Search: Efficient Inference-Time Scaling for Reward-Aligned Image Generation

arXiv Feb 3, 2026
Inference-time scaling offers a versatile paradigm for aligning visual generative models with downstream objectives without parameter updates. However, existing approaches that optimize the high-dimensional initial noise suffer from severe inefficien... read more 
Machine Learning cs.CV

VIRAL: Visual In-Context Reasoning via Analogy in Diffusion Transformers

arXiv Feb 3, 2026
Replicating In-Context Learning (ICL) in computer vision remains challenging due to task heterogeneity. We propose \textbf{VIRAL}, a framework that elicits visual reasoning from a pre-trained image editing model by formulating ICL as conditional gene... read more 
Computer Vision and Pattern Recognition

Latent Neural-ODE for Model-Informed Precision Dosing: Overcoming Structural Assumptions in Pharmacokinetics

arXiv Feb 3, 2026
Accurate estimation of tacrolimus exposure, quantified by the area under the concentration-time curve (AUC), is essential for precision dosing after renal transplantation. Current practice relies on population pharmacokinetic (PopPK) models based on ... read more 
Machine Learning cs.AI cs.LG

PokeFusion Attention: Enhancing Reference-Free Style-Conditioned Generation

arXiv Feb 3, 2026
This paper studies reference-free style-conditioned character generation in text-to-image diffusion models, where high-quality synthesis requires both stable character structure and consistent, fine-grained style expression across diverse prompts. Ex... read more 
Computer Vision and Pattern Recognition

Spiral RoPE: Rotate Your Rotary Positional Embeddings in the 2D Plane

arXiv Feb 3, 2026
Rotary Position Embedding (RoPE) is the de facto positional encoding in large language models due to its ability to encode relative positions and support length extrapolation. When adapted to vision transformers, the standard axial formulation decomp... read more 
Computer Vision and Pattern Recognition

EventFlash: Towards Efficient MLLMs for Event-Based Vision

arXiv Feb 3, 2026
Event-based multimodal large language models (MLLMs) enable robust perception in high-speed and low-light scenarios, addressing key limitations of frame-based MLLMs. However, current event-based MLLMs often rely on dense image-like processing paradig... read more 
Computer Vision and Pattern Recognition

HypCBC: Domain-Invariant Hyperbolic Cross-Branch Consistency for Generalizable Medical Image Analysis

arXiv Feb 3, 2026
Robust generalization beyond training distributions remains a critical challenge for deep neural networks. This is especially pronounced in medical image analysis, where data is often scarce and covariate shifts arise from different hardware devices,... read more 
Computer Vision and Pattern Recognition cs.LG eess.IV

Universal Approximation of Continuous Functionals on Compact Subsets via Linear Measurements and Scalar Nonlinearities

arXiv Feb 3, 2026
We study universal approximation of continuous functionals on compact subsets of products of Hilbert spaces. We prove that any such functional can be uniformly approximated by models that first take finitely many continuous linear measurements of the... read more 
Machine Learning math.FA
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