Artificial Intelligence Medical Compendium

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

Showing 55,851 to 55,860 of 226,731 articles

PDE-Constrained Optimization for Neural Image Segmentation with Physics Priors

arXiv Feb 1, 2026
Segmentation of microscopy images constitutes an ill-posed inverse problem due to measurement noise, weak object boundaries, and limited labeled data. Although deep neural networks provide flexible nonparametric estimators, unconstrained empirical ri... read more 
Computer Vision and Pattern Recognition cs.LG

PISA: Piecewise Sparse Attention Is Wiser for Efficient Diffusion Transformers

arXiv Feb 1, 2026
Diffusion Transformers are fundamental for video and image generation, but their efficiency is bottlenecked by the quadratic complexity of attention. While block sparse attention accelerates computation by attending only critical key-value blocks, it... read more 
Computer Vision and Pattern Recognition

AutoHealth: An Uncertainty-Aware Multi-Agent System for Autonomous Health Data Modeling

arXiv Feb 1, 2026
LLM-based agents have demonstrated strong potential for autonomous machine learning, yet their applicability to health data remains limited. Existing systems often struggle to generalize across heterogeneous health data modalities, rely heavily on pr... read more 
Artificial Intelligence

MedAD-R1: Eliciting Consistent Reasoning in Interpretible Medical Anomaly Detection via Consistency-Reinforced Policy Optimization

arXiv Feb 1, 2026
Medical Anomaly Detection (MedAD) presents a significant opportunity to enhance diagnostic accuracy using Large Multimodal Models (LMMs) to interpret and answer questions based on medical images. However, the reliance on Supervised Fine-Tuning (SFT) ... read more 
Computer Vision and Pattern Recognition

Differential Vector Erasure: Unified Training-Free Concept Erasure for Flow Matching Models

arXiv Feb 1, 2026
Text-to-image diffusion models have demonstrated remarkable capabilities in generating high-quality images, yet their tendency to reproduce undesirable concepts, such as NSFW content, copyrighted styles, or specific objects, poses growing concerns fo... read more 
Computer Vision and Pattern Recognition

PandaPose: 3D Human Pose Lifting from a Single Image via Propagating 2D Pose Prior to 3D Anchor Space

arXiv Feb 1, 2026
3D human pose lifting from a single RGB image is a challenging task in 3D vision. Existing methods typically establish a direct joint-to-joint mapping from 2D to 3D poses based on 2D features. This formulation suffers from two fundamental limitations... read more 
Computer Vision and Pattern Recognition

Robust Harmful Meme Detection under Missing Modalities via Shared Representation Learning

arXiv Feb 1, 2026
Internet memes are powerful tools for communication, capable of spreading political, psychological, and sociocultural ideas. However, they can be harmful and can be used to disseminate hate toward targeted individuals or groups. Although previous stu... read more 
Computer Vision and Pattern Recognition

OLion: Approaching the Hadamard Ideal by Intersecting Spectral and $\ell_{\infty}$ Implicit Biases

arXiv Feb 1, 2026
Many optimizers can be interpreted as steepest-descent methods under norm-induced geometries, and thus inherit corresponding implicit biases. We introduce \nameA{} (\fullname{}), which combines spectral control from orthogonalized update directions w... read more 
Machine Learning cs.AI

LightCity: An Urban Dataset for Outdoor Inverse Rendering and Reconstruction under Multi-illumination Conditions

arXiv Feb 1, 2026
Inverse rendering in urban scenes is pivotal for applications like autonomous driving and digital twins. Yet, it faces significant challenges due to complex illumination conditions, including multi-illumination and indirect light and shadow effects. ... read more 
Computer Vision and Pattern Recognition

ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs

arXiv Feb 1, 2026
Dynamic graph representation learning requires capturing both structural relationships and temporal evolution, yet existing approaches face a fundamental trade-off: attention-based methods achieve expressiveness at $O(T^2)$ complexity, while recurren... read more 
Machine Learning
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