Artificial Intelligence Medical Compendium

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

Showing 47,331 to 47,340 of 224,199 articles

AeroDGS: Physically Consistent Dynamic Gaussian Splatting for Single-Sequence Aerial 4D Reconstruction

arXiv Feb 25, 2026
Recent advances in 4D scene reconstruction have significantly improved dynamic modeling across various domains. However, existing approaches remain limited under aerial conditions with single-view capture, wide spatial range, and dynamic objects of l... read more 
Computer Vision and Pattern Recognition cs.AI

Enhancing Renal Tumor Malignancy Prediction: Deep Learning with Automatic 3D CT Organ Focused Attention

arXiv Feb 25, 2026
Accurate prediction of malignancy in renal tumors is crucial for informing clinical decisions and optimizing treatment strategies. However, existing imaging modalities lack the necessary accuracy to reliably predict malignancy before surgical interve... read more 
Computer Vision and Pattern Recognition cs.AI

Predicting Multi-Drug Resistance in Bacterial Isolates Through Performance Comparison and LIME-based Interpretation of Classification Models

arXiv Feb 25, 2026
The rise of Antimicrobial Resistance, particularly Multi-Drug Resistance (MDR), presents a critical challenge for clinical decision-making due to limited treatment options and delays in conventional susceptibility testing. This study proposes an inte... read more 
Machine Learning

CLIP Is Shortsighted: Paying Attention Beyond the First Sentence

arXiv Feb 25, 2026
CLIP models learn transferable multi-modal features via image-text contrastive learning on internet-scale data. They are widely used in zero-shot classification, multi-modal retrieval, text-to-image diffusion, and as image encoders in large vision-la... read more 
Computer Vision and Pattern Recognition

SimpleOCR: Rendering Visualized Questions to Teach MLLMs to Read

arXiv Feb 25, 2026
Despite the rapid advancements in Multimodal Large Language Models (MLLMs), a critical question regarding their visual grounding mechanism remains unanswered: do these models genuinely ``read'' text embedded in images, or do they merely rely on param... read more 
Computer Vision and Pattern Recognition cs.LG

Calibrated Test-Time Guidance for Bayesian Inference

arXiv Feb 25, 2026
Test-time guidance is a widely used mechanism for steering pretrained diffusion models toward outcomes specified by a reward function. Existing approaches, however, focus on maximizing reward rather than sampling from the true Bayesian posterior, lea... read more 
Machine Learning cs.AI

MammoWise: Multi-Model Local RAG Pipeline for Mammography Report Generation

arXiv Feb 25, 2026
Screening mammography is high volume, time sensitive, and documentation heavy. Radiologists must translate subtle visual findings into consistent BI-RADS assessments, breast density categories, and structured narrative reports. While recent Vision La... read more 
Computer Vision and Pattern Recognition cs.IR

Beyond Dominant Patches: Spatial Credit Redistribution For Grounded Vision-Language Models

arXiv Feb 25, 2026
Vision-language models (VLMs) frequently hallucinate objects absent from the input image. We trace this failure to spatial credit collapse: activation credit concentrating on sparse visual patches in early transformer layers, which suppresses context... read more 
Computer Vision and Pattern Recognition cs.AI

Flow Matching is Adaptive to Manifold Structures

arXiv Feb 25, 2026
Flow matching has emerged as a simulation-free alternative to diffusion-based generative modeling, producing samples by solving an ODE whose time-dependent velocity field is learned along an interpolation between a simple source distribution (e.g., a... read more 
Machine Learning cs.LG math.ST

Explainability-Aware Evaluation of Transfer Learning Models for IoT DDoS Detection Under Resource Constraints

arXiv Feb 25, 2026
Distributed denial-of-service (DDoS) attacks threaten the availability of Internet of Things (IoT) infrastructures, particularly under resource-constrained deployment conditions. Although transfer learning models have shown promising detection accura... read more 
Cryptography and Security cs.AI
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