Artificial Intelligence Medical Compendium

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

Showing 45,891 to 45,900 of 224,055 articles

Exploring factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients based on pre-dialysis parameters.

Clinical nephrology Mar 1, 2026
OBJECTIVE: This study explored factors and models to predict post-dialysis volume overload status in maintenance hemodialysis patients (MHD) based on pre-dialysis parameters using machine learning. MATERIALS AND METHODS: Pre-dialysis clinical data, p... read more 

Renal interstitial inflammation predicts IgA nephropathy progression via multiple machine learning models.

Clinical nephrology Mar 1, 2026
BACKGROUND: Renal interstitial inflammation (RII) is a frequent pathological feature in IgA nephropathy (IgAN), but its prognostic value remains uncertain. This study investigated the effect of RII on renal outcomes and developed a machine learning-b... read more 

Body Charts from CT Segmentations across the Adult Lifespan: Large-scale Cross-sectional and Longitudinal Analyses.

Radiology. Artificial intelligence Mar 1, 2026
Purpose To model the distribution of CT-derived whole-body anatomic volumes across adulthood and establish comprehensive cross-sectional and longitudinal reference charts, addressing the current lack of nonbrain CT-based whole-body standards. Materia... read more 

Impact of Label Noise from Large Language Model-generated Annotations on Evaluation of Diagnostic Model Performance.

Radiology. Artificial intelligence Mar 1, 2026
Purpose To systematically examine how large language model (LLM)-generated label noise impacts real-world evaluation of artificial intelligence (AI) binary classification model performance. Materials and Methods A simulation framework was developed t... read more 

Versatile Backdoor Attack With Visible, Semantic, Sample-Specific and Compatible Triggers.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Deep neural networks (DNNs) can be manipulated to exhibit specific behaviors when exposed to specific trigger patterns, without affecting their performance on benign samples, dubbed backdoor attack. Currently, implementing backdoor attacks in physica... read more 

CMKD: CNN/Transformer-Based Cross-Model Knowledge Distillation for Audio Classification.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Audio classification is an active research area with a wide range of applications. Over the past decade, convolutional neural networks (CNNs) have been the de-facto standard building block for end-to-end audio classification models. Recently, neural ... read more 

Adverse reactions of PD-1/PD-L1 inhibitors in cancer: FAERS database analysis and protocols to mitigate immune-related events in elderly patients and when using pembrolizumab and atezolizumab.

International journal of clinical pharmacology and therapeutics Mar 1, 2026
OBJECTIVE: This study aimed to characterize adverse drug reactions (ADRs) associated with programmed death-1/programmed death-ligand 1 (PD-1/PD-L1) inhibitors in cancer immunotherapy, identifying demographic, pharmacological, and clinical determinant... read more 

Homophily Edge Augment Graph Neural Network for High-Class Homophily Variance Learning.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Graph Neural Networks (GNNs) have achieved remarkable success in machine learning tasks by learning the features of graph data. However, experiments show that vanilla GNNs fail to achieve good classification performance in the field of graph anomaly ... read more 

Heatmap Pooling Network for Action Recognition From RGB Videos.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Human action recognition (HAR) in videos has garnered widespread attention due to the rich information in RGB videos. Nevertheless, existing methods for extracting deep features from RGB videos face challenges such as information redundancy, suscepti... read more 

Physics-Informed Matrix Factorization Operator.

IEEE transactions on pattern analysis and machine intelligence Mar 1, 2026
Matrix factorization is a fundamental characterization model in machine learning and is usually solved using mathematical decomposition reconstruction loss. However, matrix factorization is a data-driven model whose results depend on data quality, ma... read more 
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