Artificial Intelligence Medical Compendium

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

Showing 52,041 to 52,050 of 225,279 articles

EVA: Towards a universal model of the immune system

arXiv Feb 10, 2026
The effective application of foundation models to translational research in immune-mediated diseases requires multimodal patient-level representations that can capture complex phenotypes emerging from multicellular interactions. Yet most current biol... read more 
Quantitative Methods cs.AI cs.LG

When the Prompt Becomes Visual: Vision-Centric Jailbreak Attacks for Large Image Editing Models

arXiv Feb 10, 2026
Recent advances in large image editing models have shifted the paradigm from text-driven instructions to vision-prompt editing, where user intent is inferred directly from visual inputs such as marks, arrows, and visual-text prompts. While this parad... read more 
Computer Vision and Pattern Recognition cs.AI

Adaptive Optimization via Momentum on Variance-Normalized Gradients

arXiv Feb 10, 2026
We introduce MVN-Grad (Momentum on Variance-Normalized Gradients), an Adam-style optimizer that improves stability and performance by combining two complementary ideas: variance-based normalization and momentum applied after normalization. MVN-Grad s... read more 
Machine Learning math.OC

How Much Reasoning Do Retrieval-Augmented Models Add beyond LLMs? A Benchmarking Framework for Multi-Hop Inference over Hybrid Knowledge

arXiv Feb 10, 2026
Large language models (LLMs) continue to struggle with knowledge-intensive questions that require up-to-date information and multi-hop reasoning. Augmenting LLMs with hybrid external knowledge, such as unstructured text and structured knowledge graph... read more 
Machine Learning

ELROND: Exploring and decomposing intrinsic capabilities of diffusion models

arXiv Feb 10, 2026
A single text prompt passed to a diffusion model often yields a wide range of visual outputs determined solely by stochastic process, leaving users with no direct control over which specific semantic variations appear in the image. While existing uns... read more 
Machine Learning

Kernel-Based Learning of Chest X-ray Images for Predicting ICU Escalation among COVID-19 Patients

arXiv Feb 10, 2026
Kernel methods have been extensively utilized in machine learning for classification and prediction tasks due to their ability to capture complex non-linear data patterns. However, single kernel approaches are inherently limited, as they rely on a si... read more 
Machine Learning stat.AP stat.ML

Colorimeter-Supervised Skin Tone Estimation from Dermatoscopic Images for Fairness Auditing

arXiv Feb 10, 2026
Neural-network-based diagnosis from dermatoscopic images is increasingly used for clinical decision support, yet studies report performance disparities across skin tones. Fairness auditing of these models is limited by the lack of reliable skin-tone ... read more 
Computer Vision and Pattern Recognition

From Classical to Topological Neural Networks Under Uncertainty

arXiv Feb 10, 2026
This chapter explores neural networks, topological data analysis, and topological deep learning techniques, alongside statistical Bayesian methods, for processing images, time series, and graphs to maximize the potential of artificial intelligence in... read more 
Machine Learning cs.AI

ERGO: Excess-Risk-Guided Optimization for High-Fidelity Monocular 3D Gaussian Splatting

arXiv Feb 10, 2026
Generating 3D content from a single image remains a fundamentally challenging and ill-posed problem due to the inherent absence of geometric and textural information in occluded regions. While state-of-the-art generative models can synthesize auxilia... read more 
Computer Vision and Pattern Recognition cs.AI

ICODEN: Ordinary Differential Equation Neural Networks for Interval-Censored Data

arXiv Feb 10, 2026
Predicting time-to-event outcomes when event times are interval censored is challenging because the exact event time is unobserved. Many existing survival analysis approaches for interval-censored data rely on strong model assumptions or cannot handl... read more 
Machine Learning q-bio.QM stat.ML
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