Artificial Intelligence Medical Compendium

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

Showing 49,981 to 49,990 of 224,814 articles

MB-DSMIL-CL-PL: Scalable Weakly Supervised Ovarian Cancer Subtype Classification and Localisation Using Contrastive and Prototype Learning with Frozen Patch Features

arXiv Feb 16, 2026
The study of histopathological subtypes is valuable for the personalisation of effective treatment strategies for ovarian cancer. However, increasing diagnostic workloads present a challenge for UK pathology departments, leading to the rise in AI app... read more 
Computer Vision and Pattern Recognition cs.AI

Learning Representations from Incomplete EHR Data with Dual-Masked Autoencoding

arXiv Feb 16, 2026
Learning from electronic health records (EHRs) time series is challenging due to irregular sam- pling, heterogeneous missingness, and the resulting sparsity of observations. Prior self-supervised meth- ods either impute before learning, represent mis... read more 
Machine Learning

Distributional Deep Learning for Super-Resolution of 4D Flow MRI under Domain Shift

arXiv Feb 16, 2026
Super-resolution is widely used in medical imaging to enhance low-quality data, reducing scan time and improving abnormality detection. Conventional super-resolution approaches typically rely on paired datasets of downsampled and original high resolu... read more 
Computer Vision and Pattern Recognition stat.AP stat.ML

Time-Archival Camera Virtualization for Sports and Visual Performances

arXiv Feb 16, 2026
Camera virtualization -- an emerging solution to novel view synthesis -- holds transformative potential for visual entertainment, live performances, and sports broadcasting by enabling the generation of photorealistic images from novel viewpoints usi... read more 
Computer Vision and Pattern Recognition cs.LG cs.RO

Seeing to Generalize: How Visual Data Corrects Binding Shortcuts

arXiv Feb 16, 2026
Vision Language Models (VLMs) are designed to extend Large Language Models (LLMs) with visual capabilities, yet in this work we observe a surprising phenomenon: VLMs can outperform their underlying LLMs on purely text-only tasks, particularly in long... read more 
Machine Learning cs.CL

Weight space Detection of Backdoors in LoRA Adapters

arXiv Feb 16, 2026
LoRA adapters let users fine-tune large language models (LLMs) efficiently. However, LoRA adapters are shared through open repositories like Hugging Face Hub \citep{huggingface_hub_docs}, making them vulnerable to backdoor attacks. Current detection ... read more 
Cryptography and Security cs.AI cs.CL cs.LG

BindCLIP: A Unified Contrastive-Generative Representation Learning Framework for Virtual Screening

arXiv Feb 16, 2026
Virtual screening aims to efficiently identify active ligands from massive chemical libraries for a given target pocket. Recent CLIP-style models such as DrugCLIP enable scalable virtual screening by embedding pockets and ligands into a shared space.... read more 
Machine Learning

Scaling Laws for Masked-Reconstruction Transformers on Single-Cell Transcriptomics

arXiv Feb 16, 2026
Neural scaling laws -- power-law relationships between loss, model size, and data -- have been extensively documented for language and vision transformers, yet their existence in single-cell genomics remains largely unexplored. We present the first s... read more 
Machine Learning q-bio.GN

SEG-JPEG: Simple Visual Semantic Communications for Remote Operation of Automated Vehicles over Unreliable Wireless Networks

arXiv Feb 16, 2026
Remote Operation is touted as being key to the rapid deployment of automated vehicles. Streaming imagery to control connected vehicles remotely currently requires a reliable, high throughput network connection, which can be limited in real-world remo... read more 
Robotics

Towards an objective classification of pachychoroid disease and its risk of progression.

Eye (London, England) Feb 16, 2026
PURPOSE: To identify clinical phenotypes in pachychoroid disease (PD), characterise long-term progression patterns, and evaluate the effect of photodynamic therapy (PDT) using machine learning and longitudinal probabilistic modelling. METHODS: This r... read more 
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