Artificial Intelligence Medical Compendium

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

Showing 58,971 to 58,980 of 227,876 articles

Towards Realistic Remote Sensing Dataset Distillation with Discriminative Prototype-guided Diffusion

arXiv Jan 22, 2026
Recent years have witnessed the remarkable success of deep learning in remote sensing image interpretation, driven by the availability of large-scale benchmark datasets. However, this reliance on massive training data also brings two major challenges... read more 
Computer Vision and Pattern Recognition

RF Intelligence for Health: Classification of SmartBAN Signals in overcrowded ISM band

arXiv Jan 22, 2026
Accurate classification of Radio-Frequency (RF) signals is essential for reliable wearable health-monitoring systems, providing awareness of the interference conditions in which medical protocols operate. In the overcrowded 2.4 GHz ISM band, however,... read more 
Networking and Internet Architecture

Determinants of Training Corpus Size for Clinical Text Classification

arXiv Jan 22, 2026
Introduction: Clinical text classification using natural language processing (NLP) models requires adequate training data to achieve optimal performance. For that, 200-500 documents are typically annotated. The number is constrained by time and costs... read more 
Computation and Language cs.LG

Uncertainty-guided Generation of Dark-field Radiographs

arXiv Jan 22, 2026
X-ray dark-field radiography provides complementary diagnostic information to conventional attenuation imaging by visualizing microstructural tissue changes through small-angle scattering. However, the limited availability of such data poses challeng... read more 
Machine Learning cs.CV

A Lightweight Brain-Inspired Machine Learning Framework for Coronary Angiography: Hybrid Neural Representation and Robust Learning Strategies

arXiv Jan 22, 2026
Background: Coronary angiography (CAG) is a cornerstone imaging modality for assessing coronary artery disease and guiding interventional treatment decisions. However, in real-world clinical settings, angiographic images are often characterized by co... read more 
Computer Vision and Pattern Recognition cs.LG

Out-of-Distribution Detection Based on Total Variation Estimation

arXiv Jan 22, 2026
This paper introduces a novel approach to securing machine learning model deployments against potential distribution shifts in practical applications, the Total Variation Out-of-Distribution (TV-OOD) detection method. Existing methods have produced s... read more 
Computer Vision and Pattern Recognition

PMPBench: A Paired Multi-Modal Pan-Cancer Benchmark for Medical Image Synthesis

arXiv Jan 22, 2026
Contrast medium plays a pivotal role in radiological imaging, as it amplifies lesion conspicuity and improves detection for the diagnosis of tumor-related diseases. However, depending on the patient's health condition or the medical resources availab... read more 
Computer Vision and Pattern Recognition

Understanding the Transfer Limits of Vision Foundation Models

arXiv Jan 22, 2026
Foundation models leverage large-scale pretraining to capture extensive knowledge, demonstrating generalization in a wide range of language tasks. By comparison, vision foundation models (VFMs) often exhibit uneven improvements across downstream task... read more 
Computer Vision and Pattern Recognition cs.AI

RadJEPA: Radiology Encoder for Chest X-Rays via Joint Embedding Predictive Architecture

arXiv Jan 22, 2026
Recent advances in medical vision language models guide the learning of visual representations; however, this form of supervision is constrained by the availability of paired image text data, raising the question of whether robust radiology encoders ... read more 
Computer Vision and Pattern Recognition

Transfer Learning from ImageNet for MEG-Based Decoding of Imagined Speech

arXiv Jan 22, 2026
Non-invasive decoding of imagined speech remains challenging due to weak, distributed signals and limited labeled data. Our paper introduces an image-based approach that transforms magnetoencephalography (MEG) signals into time-frequency representati... read more 
Computation and Language cs.AI cs.CV
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