Artificial Intelligence Medical Compendium

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

Showing 45,761 to 45,770 of 224,055 articles

Revisiting Transformation Invariant Geometric Deep Learning: An Initial Representation Perspective.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Deep neural networks have achieved great success in the last decade. When designing neural networks to handle the ubiquitous geometric data such as point clouds and graphs, it is critical that the model can maintain invariance towards various transfo... read more 

Joint Sparse Optical Flow Estimation and Keypoint Detection via Dual-task Imperative Learning.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Contemporary deep learning approaches for optical flow estimation continue to face persistent challenges in model interpretability, generalization capacity, and deployment efficiency, significantly constraining their practical implementation. This li... read more 

OoDBench+: Quantifying and Understanding Two Dimensions of Out-of-Distribution Generalization.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Deep learning has demonstrated remarkable generalization capability with independent and identically distributed (i.i.d.) training and test data, however, it often struggles with data drawn from different, albeit causally related, distributions. This... read more 

MsM-DPM: Multiscale Mamba Diffusion Probabilistic Model for Medical Image Segmentation.

IEEE transactions on cybernetics Mar 1, 2026
Diffusion probabilistic models (DPMs) have recently demonstrated promising performance in medical image segmentation. However, traditional DPM has difficulty handling the irregular structure of images and the inherent similarity between lesions and s... read more 

IML-Spikeformer: Input-Aware Multilevel Spiking Transformer for Speech Processing.

IEEE transactions on neural networks and learning systems Mar 1, 2026
Spiking neural networks (SNNs), inspired by biological neural mechanisms, represent a promising neuromorphic computing paradigm that offers energy-efficient alternatives to traditional artificial neural networks (ANNs). Despite proven effectiveness, ... read more 

Multimodal Cross-City Semantic Segmentation Based on Similarity-Inspired Fusion and Invertible Transformation Learning Network.

IEEE transactions on neural networks and learning systems Mar 1, 2026
Multimodal cross-city semantic segmentation aims to adapt a network trained on multiple labeled source domains (MSDs) from one city to multiple unlabeled target domains (MTDs) in another city, where the multiple domains refer to different sensor moda... read more 

Causality-Driven Convolutional Manifold Attention Network for Electroencephalogram Signal Decoding.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Deep learning-based methods have achieved remarkable success in brain-computer interfaces (BCIs). However, its inherent assumption of independent and identically distributed (i.i.d.) data renders it vulnerable to out-of-distribution (OOD) scenarios. ... read more 

DIAGNOSTIC PERFORMANCE OF MACHINE LEARNING TECHNOLOGY USING OPTICAL COHERENCE TOMOGRAPHIC IMAGE IN RETINAL DISEASES PRESENTED WITH SUBRETINAL FLUID.

Retina (Philadelphia, Pa.) Mar 1, 2026
PURPOSE: To study the diagnostic performance of machine learning in the diagnosis of three retinal diseases presented with subretinal fluid: central serous chorioretinopathy, polypoidal choroidal vasculopathy, and Vogt-Koyanagi-Harada disease by usin... read more 

Energy-Based Model for Accurate Estimation of Shapley Values in Feature Attribution.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Shapley value is a widely used tool in explainable artificial intelligence (XAI), as it provides a principled way to attribute contributions of input features to model outputs. However, estimation of Shapley value requires capturing conditional depen... read more 

DynamicPAE: Generating Scene-Aware Physical Adversarial Examples in Real-Time.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Physical adversarial examples (PAEs) are regarded as "whistle-blowers" of real-world risks in deep-learning applications, thus worth further investigation. However, current PAE generation studies show limited adaptive attacking ability to diverse and... read more 
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