Artificial Intelligence Medical Compendium

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

Showing 60,051 to 60,060 of 228,014 articles

Race, Ethnicity and Their Implication on Bias in Large Language Models

arXiv Jan 19, 2026
Large language models (LLMs) increasingly operate in high-stakes settings including healthcare and medicine, where demographic attributes such as race and ethnicity may be explicitly stated or implicitly inferred from text. However, existing studies ... read more 
Computation and Language cs.LG

PDFInspect: A Unified Feature Extraction Framework for Malicious Document Detection

arXiv Jan 19, 2026
The increasing prevalence of malicious Portable Document Format (PDF) files necessitates robust and comprehensive feature extraction techniques for effective detection and analysis. This work presents a unified framework that integrates graph-based, ... read more 
Cryptography and Security cs.LG

Proxy Robustness in Vision Language Models is Effortlessly Transferable

arXiv Jan 19, 2026
As a pivotal technique for improving the defense of deep models, adversarial robustness transfer via distillation has demonstrated remarkable success in conventional image classification tasks. However, this paradigm encounters critical challenges wh... read more 
Computer Vision and Pattern Recognition

Accurate Simulation Pipeline for Passive Single-Photon Imaging

arXiv Jan 19, 2026
Single-Photon Avalanche Diodes (SPADs) are new and promising imaging sensors. These sensors are sensitive enough to detect individual photons hitting each pixel, with extreme temporal resolution and without readout noise. Thus, SPADs stand out as an ... read more 
Instrumentation and Detectors cs.CV

Seeing Isn't Always Believing: Analysis of Grad-CAM Faithfulness and Localization Reliability in Lung Cancer CT Classification

arXiv Jan 19, 2026
Explainable Artificial Intelligence (XAI) techniques, such as Gradient-weighted Class Activation Mapping (Grad-CAM), have become indispensable for visualizing the reasoning process of deep neural networks in medical image analysis. Despite their popu... read more 
Computer Vision and Pattern Recognition

TreeDGS: Aerial Gaussian Splatting for Distant DBH Measurement

arXiv Jan 19, 2026
Aerial remote sensing enables efficient large-area surveying, but accurate direct object-level measurement remains difficult in complex natural scenes. Recent advancements in 3D vision, particularly learned radiance-field representations such as NeRF... read more 
Computer Vision and Pattern Recognition

A Generalist Foundation Model for Total-body PET/CT Enables Diagnostic Reporting and System-wide Metabolic Profiling

arXiv Jan 19, 2026
Total-body PET/CT enables system-wide molecular imaging, but heterogeneous anatomical and metabolic signals, approximately 2 m axial coverage, and structured radiology semantics challenge existing medical AI models that assume single-modality inputs,... read more 
Computer Vision and Pattern Recognition

Left-Right Symmetry Breaking in CLIP-style Vision-Language Models Trained on Synthetic Spatial-Relation Data

arXiv Jan 19, 2026
Spatial understanding remains a key challenge in vision-language models. Yet it is still unclear whether such understanding is truly acquired, and if so, through what mechanisms. We present a controllable 1D image-text testbed to probe how left-right... read more 
Computer Vision and Pattern Recognition cs.AI cs.LG

Joint Source-Channel-Generation Coding: From Distortion-oriented Reconstruction to Semantic-consistent Generation

arXiv Jan 19, 2026
Conventional communication systems, including both separation-based coding and AI-driven joint source-channel coding (JSCC), are largely guided by Shannon's rate-distortion theory. However, relying on generic distortion metrics fails to capture compl... read more 
Information Theory cs.CV cs.LG

SL-CBM: Enhancing Concept Bottleneck Models with Semantic Locality for Better Interpretability

arXiv Jan 19, 2026
Explainable AI (XAI) is crucial for building transparent and trustworthy machine learning systems, especially in high-stakes domains. Concept Bottleneck Models (CBMs) have emerged as a promising ante-hoc approach that provides interpretable, concept-... read more 
Artificial Intelligence cs.LG
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