Artificial Intelligence Medical Compendium

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

Showing 57,881 to 57,890 of 227,388 articles

GimmBO: Interactive Generative Image Model Merging via Bayesian Optimization

arXiv Jan 26, 2026
Fine-tuning-based adaptation is widely used to customize diffusion-based image generation, leading to large collections of community-created adapters that capture diverse subjects and styles. Adapters derived from the same base model can be merged wi... read more 
Computer Vision and Pattern Recognition cs.GR

AGSP-DSA: An Adaptive Graph Signal Processing Framework for Robust Multimodal Fusion with Dynamic Semantic Alignment

arXiv Jan 26, 2026
In this paper, we introduce an Adaptive Graph Signal Processing with Dynamic Semantic Alignment (AGSP DSA) framework to perform robust multimodal data fusion over heterogeneous sources, including text, audio, and images. The requested approach uses a... read more 
Computer Vision and Pattern Recognition cs.MM

LaCoGSEA: Unsupervised deep learning for pathway analysis via latent correlation

arXiv Jan 26, 2026
Motivation: Pathway enrichment analysis is widely used to interpret gene expression data. Standard approaches, such as GSEA, rely on predefined phenotypic labels and pairwise comparisons, which limits their applicability in unsupervised settings. Exi... read more 
Machine Learning q-bio.GN

Geometry-Free Conditional Diffusion Modeling for Solving the Inverse Electrocardiography Problem

arXiv Jan 26, 2026
This paper proposes a data-driven model for solving the inverse problem of electrocardiography, the mathematical problem that forms the basis of electrocardiographic imaging (ECGI). We present a conditional diffusion framework that learns a probabili... read more 
Machine Learning

Issues regarding the Indexing of Publication Types and Study Designs

arXiv Jan 26, 2026
Objectives. Major research and implementation efforts have been devoted to indexing articles according to the major topics discussed, but much less effort to indexing their publication types and study designs (collectively, PTs). In this Perspective,... read more 
Digital Libraries

Scale-Aware Self-Supervised Learning for Segmentation of Small and Sparse Structures

arXiv Jan 26, 2026
Self-supervised learning (SSL) has emerged as a powerful strategy for representation learning under limited annotation regimes, yet its effectiveness remains highly sensitive to many factors, especially the nature of the target task. In segmentation,... read more 
Computer Vision and Pattern Recognition

Adaptive Domain Shift in Diffusion Models for Cross-Modality Image Translation

arXiv Jan 26, 2026
Cross-modal image translation remains brittle and inefficient. Standard diffusion approaches often rely on a single, global linear transfer between domains. We find that this shortcut forces the sampler to traverse off-manifold, high-cost regions, in... read more 
Computer Vision and Pattern Recognition

CONQUER: Context-Aware Representation with Query Enhancement for Text-Based Person Search

arXiv Jan 26, 2026
Text-Based Person Search (TBPS) aims to retrieve pedestrian images from large galleries using natural language descriptions. This task, essential for public safety applications, is hindered by cross-modal discrepancies and ambiguous user queries. We ... read more 
Computer Vision and Pattern Recognition

Splat-Portrait: Generalizing Talking Heads with Gaussian Splatting

arXiv Jan 26, 2026
Talking Head Generation aims at synthesizing natural-looking talking videos from speech and a single portrait image. Previous 3D talking head generation methods have relied on domain-specific heuristics such as warping-based facial motion representat... read more 
Computer Vision and Pattern Recognition

TwinPurify: Purifying gene expression data to reveal tumor-intrinsic transcriptional programs via self-supervised learning

arXiv Jan 26, 2026
Advances in single-cell and spatial transcriptomic technologies have transformed tumor ecosystem profiling at cellular resolution. However, large scale studies on patient cohorts continue to rely on bulk transcriptomic data, where variation in tumor ... read more 
Machine Learning q-bio.MN
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