Artificial Intelligence Medical Compendium

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

Showing 53,631 to 53,640 of 225,548 articles

An Intuitionistic Fuzzy Logic Driven UNet architecture: Application to Brain Image segmentation

arXiv Feb 4, 2026
Accurate segmentation of MRI brain images is essential for image analysis, diagnosis of neuro-logical disorders and medical image computing. In the deep learning approach, the convolutional neural networks (CNNs), especially UNet, are widely applied ... read more 
Computer Vision and Pattern Recognition

Continuous Degradation Modeling via Latent Flow Matching for Real-World Super-Resolution

arXiv Feb 4, 2026
While deep learning-based super-resolution (SR) methods have shown impressive outcomes with synthetic degradation scenarios such as bicubic downsampling, they frequently struggle to perform well on real-world images that feature complex, nonlinear de... read more 
Computer Vision and Pattern Recognition

Partial Ring Scan: Revisiting Scan Order in Vision State Space Models

arXiv Feb 4, 2026
State Space Models (SSMs) have emerged as efficient alternatives to attention for vision tasks, offering lineartime sequence processing with competitive accuracy. Vision SSMs, however, require serializing 2D images into 1D token sequences along a pre... read more 
Computer Vision and Pattern Recognition

Improving 2D Diffusion Models for 3D Medical Imaging with Inter-Slice Consistent Stochasticity

arXiv Feb 4, 2026
3D medical imaging is in high demand and essential for clinical diagnosis and scientific research. Currently, diffusion models (DMs) have become an effective tool for medical imaging reconstruction thanks to their ability to learn rich, high-quality ... read more 
Computer Vision and Pattern Recognition cs.AI eess.IV

Context Determines Optimal Architecture in Materials Segmentation

arXiv Feb 4, 2026
Segmentation architectures are typically benchmarked on single imaging modalities, obscuring deployment-relevant performance variations: an architecture optimal for one modality may underperform on another. We present a cross-modal evaluation framewo... read more 
Computer Vision and Pattern Recognition

JSynFlow: Japanese Synthesised Flowchart Visual Question Answering Dataset built with Large Language Models

arXiv Feb 4, 2026
Vision and language models (VLMs) are expected to analyse complex documents, such as those containing flowcharts, through a question-answering (QA) interface. The ability to recognise and interpret these flowcharts is in high demand, as they provide ... read more 
Computer Vision and Pattern Recognition cs.AI

Scalable Explainability-as-a-Service (XaaS) for Edge AI Systems

arXiv Feb 4, 2026
Though Explainable AI (XAI) has made significant advancements, its inclusion in edge and IoT systems is typically ad-hoc and inefficient. Most current methods are "coupled" in such a way that they generate explanations simultaneously with model infer... read more 
Machine Learning cs.AI cs.DC cs.SE

DMS2F-HAD: A Dual-branch Mamba-based Spatial-Spectral Fusion Network for Hyperspectral Anomaly Detection

arXiv Feb 4, 2026
Hyperspectral anomaly detection (HAD) aims to identify rare and irregular targets in high-dimensional hyperspectral images (HSIs), which are often noisy and unlabelled data. Existing deep learning methods either fail to capture long-range spectral de... read more 
Computer Vision and Pattern Recognition cs.AI

Influence of attention mechanisms on cerebellar and basal ganglia activity during vocal emotion decoding

bioRxiv Feb 4, 2026
Emotional prosody processing involves a widespread network of brain regions, but the specific roles of the cerebellum and basal ganglia in explicit and implicit tasks are not well known or understood. This study investigated how the cerebellum and ba... read more 
neuroscience

Large language models possess some ecologicalknowledge, but how much?

bioRxiv Feb 4, 2026
Large Language Models (LLMs) have shown remarkable capabilities in question answering across various domains, yet their effectiveness in ecological knowledge remains underexplored. Understanding their potential to recall and synthesize ecological inf... read more 
ecology
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