Artificial Intelligence Medical Compendium

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

Showing 38,081 to 38,090 of 223,469 articles

DPD-Cancer: Explainable Graph-based Deep Learning for Small Molecule Anti-Cancer Activity Prediction

arXiv Mar 27, 2026
Accurate drug response prediction is a critical bottleneck in computational biochemistry, limited by the challenge of modelling the interplay between molecular structure and cellular context. In cancer research, this is acute due to tumour heterogene... read more 
Machine Learning cs.AI

FINDER: Zero-Shot Field-Integrated Network for Distortion-free EPI Reconstruction in Diffusion MRI

arXiv Mar 27, 2026
Echo-planar imaging (EPI) remains the cornerstone of diffusion MRI, but it is prone to severe geometric distortions due to its rapid sampling scheme that renders the sequence highly sensitive to $B_{0}$ field inhomogeneities. While deep learning has ... read more 
Image and Video Processing cs.CV

SkinGPT-X: A Self-Evolving Collaborative Multi-Agent System for Transparent and Trustworthy Dermatological Diagnosis

arXiv Mar 27, 2026
While recent advancements in Large Language Models have significantly advanced dermatological diagnosis, monolithic LLMs frequently struggle with fine-grained, large-scale multi-class diagnostic tasks and rare skin disease diagnosis owing to training... read more 
Computer Vision and Pattern Recognition cs.AI

Finding Distributed Object-Centric Properties in Self-Supervised Transformers

arXiv Mar 27, 2026
Self-supervised Vision Transformers (ViTs) like DINO show an emergent ability to discover objects, typically observed in [CLS] token attention maps of the final layer. However, these maps often contain spurious activations resulting in poor localizat... read more 
Computer Vision and Pattern Recognition cs.AI cs.CL cs.LG cs.MM

TaxaAdapter: Vision Taxonomy Models are Key to Fine-grained Image Generation over the Tree of Life

arXiv Mar 27, 2026
Accurately generating images across the Tree of Life is difficult: there are over 10M distinct species on Earth, many of which differ only by subtle visual traits. Despite the remarkable progress in text-to-image synthesis, existing models often fail... read more 
Computer Vision and Pattern Recognition

IP-Bench: Benchmark for Image Protection Methods in Image-to-Video Generation Scenarios

arXiv Mar 27, 2026
With the rapid advancement of image-to-video (I2V) generation models, their potential for misuse in creating malicious content has become a significant concern. For instance, a single image can be exploited to generate a fake video, which can be used... read more 
Computer Vision and Pattern Recognition

Gaussian Shannon: High-Precision Diffusion Model Watermarking Based on Communication

arXiv Mar 27, 2026
Diffusion models generate high-quality images but pose serious risks like copyright violation and disinformation. Watermarking is a key defense for tracing and authenticating AI-generated content. However, existing methods rely on threshold-based det... read more 
Computer Vision and Pattern Recognition cs.CR

Provably Contractive and High-Quality Denoisers for Convergent Restoration

arXiv Mar 27, 2026
Image restoration, the recovery of clean images from degraded measurements, has applications in various domains like surveillance, defense, and medical imaging. Despite achieving state-of-the-art (SOTA) restoration performance, existing convolutional... read more 
Computer Vision and Pattern Recognition

CREval: An Automated Interpretable Evaluation for Creative Image Manipulation under Complex Instructions

arXiv Mar 27, 2026
Instruction-based multimodal image manipulation has recently made rapid progress. However, existing evaluation methods lack a systematic and human-aligned framework for assessing model performance on complex and creative editing tasks. To address thi... read more 
Computer Vision and Pattern Recognition

Can AI Scientist Agents Learn from Lab-in-the-Loop Feedback? Evidence from Iterative Perturbation Discovery

arXiv Mar 27, 2026
Recent work has questioned whether large language models (LLMs) can perform genuine in-context learning (ICL) for scientific experimental design, with prior studies suggesting that LLM-based agents exhibit no sensitivity to experimental feedback. We ... read more 
Machine Learning
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