Artificial Intelligence Medical Compendium

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

Showing 42,641 to 42,650 of 223,853 articles

S2D: Sparse to Dense Lifting for 3D Reconstruction with Minimal Inputs

arXiv Mar 11, 2026
Explicit 3D representations have already become an essential medium for 3D simulation and understanding. However, the most commonly used point cloud and 3D Gaussian Splatting (3DGS) each suffer from non-photorealistic rendering and significant degrad... read more 
Computer Vision and Pattern Recognition

Novel Architecture of RPA In Oral Cancer Lesion Detection

arXiv Mar 11, 2026
Accurate and early detection of oral cancer lesions is crucial for effective diagnosis and treatment. This study evaluates two RPA implementations, OC-RPAv1 and OC-RPAv2, using a test set of 31 images. OC-RPAv1 processes one image per prediction in a... read more 
Computer Vision and Pattern Recognition

Bridging the Skill Gap in Clinical CBCT Interpretation with CBCTRepD

arXiv Mar 11, 2026
Generative AI has advanced rapidly in medical report generation; however, its application to oral and maxillofacial CBCT reporting remains limited, largely because of the scarcity of high-quality paired CBCT-report data and the intrinsic complexity o... read more 
Computer Vision and Pattern Recognition

Quantifying Membership Disclosure Risk for Tabular Synthetic Data Using Kernel Density Estimators

arXiv Mar 11, 2026
The use of synthetic data has become increasingly popular as a privacy-preserving alternative to sharing real datasets, especially in sensitive domains such as healthcare, finance, and demography. However, the privacy assurances of synthetic data are... read more 
Machine Learning stat.AP

When should we trust the annotation? Selective prediction for molecular structure retrieval from mass spectra

arXiv Mar 11, 2026
Machine learning methods for identifying molecular structures from tandem mass spectra (MS/MS) have advanced rapidly, yet current approaches still exhibit significant error rates. In high-stakes applications such as clinical metabolomics and environm... read more 
Machine Learning stat.ML

Pointy - A Lightweight Transformer for Point Cloud Foundation Models

arXiv Mar 11, 2026
Foundation models for point cloud data have recently grown in capability, often leveraging extensive representation learning from language or vision. In this work, we take a more controlled approach by introducing a lightweight transformer-based poin... read more 
Computer Vision and Pattern Recognition cs.LG

Contrastive learning-based video quality assessment-jointed video vision transformer for video recognition

arXiv Mar 11, 2026
Video quality significantly affects video classification. We found this problem when we classified Mild Cognitive Impairment well from clear videos, but worse from blurred ones. From then, we realized that referring to Video Quality Assessment (VQA) ... read more 
Computer Vision and Pattern Recognition

Med-DualLoRA: Local Adaptation of Foundation Models for 3D Cardiac MRI

arXiv Mar 11, 2026
Foundation models (FMs) show great promise for robust downstream performance across medical imaging tasks and modalities, including cardiac magnetic resonance (CMR), following task-specific adaptation. However, adaptation using single-site data may l... read more 
Computer Vision and Pattern Recognition

MCMC Informed Neural Emulators for Uncertainty Quantification in Dynamical Systems

arXiv Mar 11, 2026
Neural networks are a commonly used approach to replace physical models with computationally cheap surrogates. Parametric uncertainty quantification can be included in training, assuming that an accurate prior distribution of the model parameters is ... read more 
Machine Learning

Too Vivid to Be Real? Benchmarking and Calibrating Generative Color Fidelity

arXiv Mar 11, 2026
Recent advances in text-to-image (T2I) generation have greatly improved visual quality, yet producing images that appear visually authentic to real-world photography remains challenging. This is partly due to biases in existing evaluation paradigms: ... read more 
Computer Vision and Pattern Recognition
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