Artificial Intelligence Medical Compendium

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

Showing 57,831 to 57,840 of 227,388 articles

HexFormer: Hyperbolic Vision Transformer with Exponential Map Aggregation

arXiv Jan 27, 2026
Data across modalities such as images, text, and graphs often contains hierarchical and relational structures, which are challenging to model within Euclidean geometry. Hyperbolic geometry provides a natural framework for representing such structures... read more 
Computer Vision and Pattern Recognition

RHSIA: Real-time Hemodynamics Surrogation for Non-idealized Intracranial Aneurysms

arXiv Jan 27, 2026
Extensive studies suggested that fluid mechanical markers of intracranial aneurysms (IAs) derived from Computational Fluid Dynamics (CFD) can indicate disease progression risks, but to date this has not been translated clinically. This is because CFD... read more 
Machine Learning

SONIC: Spectral Oriented Neural Invariant Convolutions

arXiv Jan 27, 2026
Convolutional Neural Networks (CNNs) rely on fixed-size kernels scanning local patches, which limits their ability to capture global context or long-range dependencies without very deep architectures. Vision Transformers (ViTs), in turn, provide glob... read more 
Computer Vision and Pattern Recognition cs.LG

VGGT-SLAM 2.0: Real time Dense Feed-forward Scene Reconstruction

arXiv Jan 27, 2026
We present VGGT-SLAM 2.0, a real time RGB feed-forward SLAM system which substantially improves upon VGGT-SLAM for incrementally aligning submaps created from VGGT. Firstly, we remove high-dimensional 15-degree-of-freedom drift and planar degeneracy ... read more 
Computer Vision and Pattern Recognition cs.RO

Riemannian AmbientFlow: Towards Simultaneous Manifold Learning and Generative Modeling from Corrupted Data

arXiv Jan 26, 2026
Modern generative modeling methods have demonstrated strong performance in learning complex data distributions from clean samples. In many scientific and imaging applications, however, clean samples are unavailable, and only noisy or linearly corrupt... read more 
Machine Learning math.DG math.OC math.ST

SeNeDiF-OOD: Semantic Nested Dichotomy Fusion for Out-of-Distribution Detection Methodology in Open-World Classification. A Case Study on Monument Style Classification

arXiv Jan 26, 2026
Out-of-distribution (OOD) detection is a fundamental requirement for the reliable deployment of artificial intelligence applications in open-world environments. However, addressing the heterogeneous nature of OOD data, ranging from low-level corrupti... read more 
Computer Vision and Pattern Recognition cs.AI

HalluGuard: Demystifying Data-Driven and Reasoning-Driven Hallucinations in LLMs

arXiv Jan 26, 2026
The reliability of Large Language Models (LLMs) in high-stakes domains such as healthcare, law, and scientific discovery is often compromised by hallucinations. These failures typically stem from two sources: data-driven hallucinations and reasoning-... read more 
Machine Learning cs.AI

ctELM: Decoding and Manipulating Embeddings of Clinical Trials with Embedding Language Models

arXiv Jan 26, 2026
Text embeddings have become an essential part of a variety of language applications. However, methods for interpreting, exploring and reversing embedding spaces are limited, reducing transparency and precluding potentially valuable generative use cas... read more 
Computation and Language cs.AI cs.LG

Semi-Supervised Hyperspectral Image Classification with Edge-Aware Superpixel Label Propagation and Adaptive Pseudo-Labeling

arXiv Jan 26, 2026
Significant progress has been made in semi-supervised hyperspectral image (HSI) classification regarding feature extraction and classification performance. However, due to high annotation costs and limited sample availability, semi-supervised learnin... read more 
Computer Vision and Pattern Recognition

Cross-Domain Transfer with Self-Supervised Spectral-Spatial Modeling for Hyperspectral Image Classification

arXiv Jan 26, 2026
Self-supervised learning has demonstrated considerable potential in hyperspectral representation, yet its application in cross-domain transfer scenarios remains under-explored. Existing methods, however, still rely on source domain annotations and ar... read more 
Computer Vision and Pattern Recognition
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