Artificial Intelligence Medical Compendium

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

Showing 43,271 to 43,280 of 224,055 articles

Hybrid Multi-View MRI Fusion for csPCa Diagnosis via Intra- and Inter-View Transformers.

IEEE journal of biomedical and health informatics Mar 10, 2026
Accurate diagnosis of clinically significant prostate cancer (csPCa) from multi-view MRI scans (axial, sagittal, and coronal) is essential for effective treatment planning and improved outcomes. Although deep learning has advanced prostate MRI analys... read more 

uBrainSurf: Unified Curvature-aware Deformation Framework for Lifespan Brain Cortical Surface Reconstruction.

IEEE transactions on medical imaging Mar 10, 2026
Accurate and automated reconstruction of cortical surfaces across the human lifespan is essential for studying brain development, aging, and the early diagnosis of neurological disorders. However, traditional neuroimaging pipelines require hours per ... read more 

Higher Order Interactions in Hub Neural Networks: Spatiotemporal Dynamics Reshaping and Control.

IEEE transactions on cybernetics Mar 10, 2026
The study of dynamics in complex systems has increasingly incorporated higher order interactions, which capture the collective influence among three or more units, extending beyond traditional pairwise connections. Although such interactions are obse... read more 

StarIR: Convolutional Image Restoration With Spatial-Frequency Fusion.

IEEE transactions on pattern analysis and machine intelligence Mar 10, 2026
Vision Transformer (ViT) has shown impressive performance in image restoration due to its ability to capture a large receptive field. However, its complexity grows quadratically with input resolution, limiting its applicability for high-resolution im... read more 

Locally Linear Continual Learning for Time Series based on VC-Theoretical Generalization Bounds.

IEEE transactions on pattern analysis and machine intelligence Mar 10, 2026
Most machine learning methods assume fixed probability distributions, limiting their applicability in nonstationary real-world scenarios. While continual learning methods address this issue, current approaches often rely on black-box models or requir... read more 

Survey of Computerized Adaptive Testing: a Machine Learning Perspective.

IEEE transactions on pattern analysis and machine intelligence Mar 10, 2026
Computerized Adaptive Testing (CAT) offers an efficient and personalized method for assessing examinee proficiency by dynamically adjusting test questions based on individual performance. Compared to traditional, non-personalized testing methods, CAT... read more 

Adaptive aggregation of Monte Carlo augmented decomposed filters for efficient group-equivariant convolutional neural network.

IEEE transactions on pattern analysis and machine intelligence Mar 10, 2026
Group-equivariant convolutional neural networks (G-CNN) heavily rely on parameter sharing to increase CNN's data efficiency and performance. However, the parameter-sharing strategy greatly increases the computational burden for each added parameter, ... read more 

Focus on Your Focus (FOYF): Cross-Domain Few-Shot Semantic Segmentation by Attention Specialization.

IEEE transactions on neural networks and learning systems Mar 10, 2026
Due to data scarcity, privacy, and security, it is difficult to obtain sufficient data to support the research and application of data-driven artificial intelligence (AI) technology across various fields. Although current few-shot semantic segmentati... read more 

Coupled Impulsive Control for Multisynchronization of Multistable Stochastic Neural Networks Under Parameter Uncertainties.

IEEE transactions on neural networks and learning systems Mar 10, 2026
Multisynchronization of multistable stochastic neural networks (MSNNs) is investigated herein. First, an MSNN multistable stochastic neural network (SNN) model subject to both time-varying delays and parameter uncertainties is constructed, which accu... read more 

A Neural-Network-Assisted Approach to Recursive State Estimation for Energy Harvesting Complex Networks With Unknown Nonlinearities.

IEEE transactions on neural networks and learning systems Mar 10, 2026
This article investigates the problem of partial node-based (PNB) recursive state estimation for complex networks (CNs) with unknown nonlinearities and energy harvesting sensors. To mitigate the effects of energy constraints, an energy replenishment ... read more 
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