Artificial Intelligence Medical Compendium

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

Showing 49,621 to 49,630 of 224,513 articles

MacNet: An End-to-End Manifold-Constrained Adaptive Clustering Network for Interpretable Whole Slide Image Classification

arXiv
Whole slide images (WSIs) are the gold standard for pathological diagnosis and sub-typing. Current main-stream two-step frameworks employ offline feature encoders trained without domain-specific knowledge. Among them, attention-based multiple instanc... read more 

MedVAR: Towards Scalable and Efficient Medical Image Generation via Next-scale Autoregressive Prediction

arXiv
Medical image generation is pivotal in applications like data augmentation for low-resource clinical tasks and privacy-preserving data sharing. However, developing a scalable generative backbone for medical imaging requires architectural efficiency, ... read more 

Efficient Text-Guided Convolutional Adapter for the Diffusion Model

arXiv
We introduce the Nexus Adapters, novel text-guided efficient adapters to the diffusion-based framework for the Structure Preserving Conditional Generation (SPCG). Recently, structure-preserving methods have achieved promising results in conditional i... read more 

OmniVTON++: Training-Free Universal Virtual Try-On with Principal Pose Guidance

arXiv
Image-based Virtual Try-On (VTON) concerns the synthesis of realistic person imagery through garment re-rendering under human pose and body constraints. In practice, however, existing approaches are typically optimized for specific data conditions, m... read more 

MATEO: A Multimodal Benchmark for Temporal Reasoning and Planning in LVLMs

arXiv
AI agents need to plan to achieve complex goals that involve orchestrating perception, sub-goal decomposition, and execution. These plans consist of ordered steps structured according to a Temporal Execution Order (TEO, a directed acyclic graph that ... read more 

OPBench: A Graph Benchmark to Combat the Opioid Crisis

arXiv
The opioid epidemic continues to ravage communities worldwide, straining healthcare systems, disrupting families, and demanding urgent computational solutions. To combat this lethal opioid crisis, graph learning methods have emerged as a promising pa... read more 

VariViT: A Vision Transformer for Variable Image Sizes

arXiv
Vision Transformers (ViTs) have emerged as the state-of-the-art architecture in representation learning, leveraging self-attention mechanisms to excel in various tasks. ViTs split images into fixed-size patches, constraining them to a predefined size... read more 

VIGIL: Tackling Hallucination Detection in Image Recontextualization

arXiv
We introduce VIGIL (Visual Inconsistency & Generative In-context Lucidity), the first benchmark dataset and framework providing a fine-grained categorization of hallucinations in the multimodal image recontextualization task for large multimodal mode... read more 

Quantum Reservoir Computing with Neutral Atoms on a Small, Complex, Medical Dataset

arXiv
Biomarker-based prediction of clinical outcomes is challenging due to nonlinear relationships, correlated features, and the limited size of many medical datasets. Classical machine-learning methods can struggle under these conditions, motivating the ... read more 

SketchingReality: From Freehand Scene Sketches To Photorealistic Images

arXiv
Recent years have witnessed remarkable progress in generative AI, with natural language emerging as the most common conditioning input. As underlying models grow more powerful, researchers are exploring increasingly diverse conditioning signals, such... read more