Artificial Intelligence Medical Compendium

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

Showing 40,591 to 40,600 of 223,737 articles

Face anonymization preserving facial expressions and photometric realism

arXiv Mar 18, 2026
The widespread sharing of face images on social media platforms and in large-scale datasets raises pressing privacy concerns, as biometric identifiers can be exploited without consent. Face anonymization seeks to generate realistic facial images that... read more 
Computer Vision and Pattern Recognition

Unsupervised Symbolic Anomaly Detection

arXiv Mar 18, 2026
We propose SYRAN, an unsupervised anomaly detection method based on symbolic regression. Instead of encoding normal patterns in an opaque, high-dimensional model, our method learns an ensemble of human-readable equations that describe symbolic invari... read more 
Machine Learning cs.AI cs.SC

LoGSAM: Parameter-Efficient Cross-Modal Grounding for MRI Segmentation

arXiv Mar 18, 2026
Precise localization and delineation of brain tumors using Magnetic Resonance Imaging (MRI) are essential for planning therapy and guiding surgical decisions. However, most existing approaches rely on task-specific supervised models and are constrain... read more 
Computer Vision and Pattern Recognition

Edit-As-Act: Goal-Regressive Planning for Open-Vocabulary 3D Indoor Scene Editing

arXiv Mar 18, 2026
Editing a 3D indoor scene from natural language is conceptually straightforward but technically challenging. Existing open-vocabulary systems often regenerate large portions of a scene or rely on image-space edits that disrupt spatial structure, resu... read more 
Computer Vision and Pattern Recognition cs.AI

Trust the Unreliability: Inward Backward Dynamic Unreliability Driven Coreset Selection for Medical Image Classification

arXiv Mar 18, 2026
Efficiently managing and utilizing large-scale medical imaging datasets with limited resources presents significant challenges. While coreset selection helps reduce computational costs, its effectiveness in medical data remains limited due to inheren... read more 
Computer Vision and Pattern Recognition

A novel stock investment strategy based on distributed k-WTA dynamic neural network.

Neural networks : the official journal of the International Neural Network Society Mar 18, 2026
This study addresses the problem of stock investment strategy, aiming to select the optimal k (k < n) stocks from a set of n stocks within a distributed topology to maximize investment returns. To this end, we propose a dynamic and adaptive neural ne... read more 

A heterogeneous encoding disentangled representation network for financial time series forecasting.

Neural networks : the official journal of the International Neural Network Society Mar 18, 2026
Financial time-series forecasting remains highly challenging due to non-stationarity, market noise, and complex dependencies across multiple temporal scales. Existing state-of-the-art models, although effective in long-sequence learning, often rely o... read more 

Density-dependent sodium-storage mechanisms in hard carbon materials.

Chemical science Mar 18, 2026
Understanding the sodium-storage mechanism in hard carbon (HC) anodes is crucial for advancing sodium-ion battery (SIB) technology. However, the intrinsic complexity of HC microstructures and their interactions with sodium remain not fully elucidated... read more 

Machine learning prediction of positive urine cultures in an academic pediatric emergency department (ED).

The American journal of emergency medicine Mar 18, 2026
BACKGROUND: Urinary tract infections (UTIs) are among the most common pediatric infections, but urine culture, the diagnostic gold standard, requires 1-3 days for results. This delay may lead to unnecessary antibiotic use or treatment delays. OBJECTI... read more 

Fast sparse supervised learning framework with BLinex loss function.

Neural networks : the official journal of the International Neural Network Society Mar 18, 2026
In this paper, a novel learning model, namely the Lp-norm sparse Blinex Twin Extreme Learning Machine (PBLTELM), is proposed, which is efficient and accurate for relatively large-scale data classification. The proposed framework incorporates three ke... read more 
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