Artificial Intelligence Medical Compendium

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

Showing 32,391 to 32,400 of 221,076 articles

Emulating Non-Differentiable Metrics via Knowledge-Guided Learning: Introducing the Minkowski Image Loss

arXiv Apr 13, 2026
The ``differentiability gap'' presents a primary bottleneck in Earth system deep learning: since models cannot be trained directly on non-differentiable scientific metrics and must rely on smooth proxies (e.g., MSE), they often fail to capture high-f... read more 
Machine Learning cs.AI

HuiYanEarth-SAR: A Foundation Model for High-Fidelity and Low-Cost Global Remote Sensing Imagery Generation

arXiv Apr 13, 2026
Synthetic Aperture Radar (SAR) imagery generation is essential for deepening the study of scattering mechanisms, establishing trustworthy electromagnetic scene models, and fundamentally alleviating the data scarcity bottleneck that constrains develop... read more 
Computer Vision and Pattern Recognition

Beyond Model Design: Data-Centric Training and Self-Ensemble for Gaussian Color Image Denoising

arXiv Apr 13, 2026
This paper presents our solution to the NTIRE 2026 Image Denoising Challenge (Gaussian color image denoising at fixed noise level $σ= 50$). Rather than proposing a new restoration backbone, we revisit the performance boundary of the mature Restormer ... read more 
Computer Vision and Pattern Recognition

TrajOnco: a multi-agent framework for temporal reasoning over longitudinal EHR for multi-cancer early detection

arXiv Apr 12, 2026
Accurate estimation of cancer risk from longitudinal electronic health records (EHRs) could support earlier detection and improved care, but modeling such complex patient trajectories remains challenging. We present TrajOnco, a training-free, multi-a... read more 
Artificial Intelligence cs.MA

Rethinking Video Human-Object Interaction: Set Prediction over Time for Unified Detection and Anticipation

arXiv Apr 12, 2026
Video-based human-object interaction (HOI) understanding requires both detecting ongoing interactions and anticipating their future evolution. However, existing methods usually treat anticipation as a downstream forecasting task built on externally c... read more 
Computer Vision and Pattern Recognition cs.AI

NameBERT: Scaling Name-Based Nationality Classification with LLM-Augmented Open Academic Data

arXiv Apr 12, 2026
Inferring nationality from personal names is a critical capability for equity and bias monitoring, personalization, and a valuable tool in biomedical and sociological research. However, existing name-based nationality classifiers are typically traine... read more 
Computation and Language

Sense Less, Infer More: Agentic Multimodal Transformers for Edge Medical Intelligence

arXiv Apr 12, 2026
Edge-based multimodal medical monitoring requires models that balance diagnostic accuracy with severe energy constraints. Continuous acquisition of ECG, PPG, EMG, and IMU streams rapidly drains wearable batteries, often limiting operation to under 10... read more 
Emerging Technologies cs.LG

CIR: Lightweight Container Image for Cross-Platform Deployment

arXiv Apr 12, 2026
In modern cloud and heterogeneous distributed infrastructures, container images are widely used as the deployment unit for machine learning applications. An image bundles the application with its entire platform-specific execution environment and can... read more 
Distributed, Parallel, and Cluster Computing

Point2Pose: Occlusion-Recovering 6D Pose Tracking and 3D Reconstruction for Multiple Unknown Objects Via 2D Point Trackers

arXiv Apr 12, 2026
We present Point2Pose, a model-free method for causal 6D pose tracking of multiple rigid objects from monocular RGB-D video. Initialized only from sparse image points on the objects to be tracked, our approach tracks multiple unseen objects without r... read more 
Computer Vision and Pattern Recognition cs.RO

CARE-ECG: Causal Agent-based Reasoning for Explainable and Counterfactual ECG Interpretation

arXiv Apr 12, 2026
Large language models (LLMs) enable waveform-to-text ECG interpretation and interactive clinical questioning, yet most ECG-LLM systems still rely on weak signal-text alignment and retrieval without explicit physiological or causal structure. This lim... read more 
Machine Learning
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