Artificial Intelligence Medical Compendium

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

Showing 5,431 to 5,440 of 205,061 articles

Proteomic signatures of early retinal neurodegeneration in type 2 diabetes mellitus.

PLoS medicine Jun 2, 2026
BACKGROUND: Retinal neurodegeneration is an early and independent feature of diabetic retinal disease and has been proposed as a window into the systemic neural consequences of diabetes, yet accessible molecular biomarkers and individualized predicti... read more 

MEG-mod: A Multiview Enhanced Graph Neural Network for Knockdown Efficiency Prediction of Chemically Modified siRNA.

Journal of medicinal chemistry Jun 2, 2026
Chemical modification is essential for improving the stability and knockdown efficiency of siRNAs. However, the combinatorial complexity of modification types and positions makes rational design difficult. Here, we propose MEG-mod, a deep learning fr... read more 

Towards Explainable Quantum AI: Informing the Encoder Selection of Quantum Neural Networks via Visualization.

IEEE transactions on visualization and computer graphics Jun 2, 2026
Quantum Neural Networks (QNNs) represent a promising fusion of quantum computing and neural network architectures, offering speed-ups and efficient processing of high-dimensional, entangled data. A crucial component of QNNs is the encoder, which maps... read more 

EfficientCovNet: Modeling the Pairwise Voxel Dependency for Brain ROI Segmentation.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society Jun 2, 2026
Segmenting the brain magnetic resonance (MR) images to region-of-interest (ROI) is a fundamental step for many medical image analysis tasks. Convolutional neural networks (CNNs) excel in learning the high-level contextual features for image segmentat... read more 

Global-Local Interaction and Recalibration Network for Salient Object Detection in Optical Remote Sensing Images.

IEEE transactions on cybernetics Jun 2, 2026
Optical remote sensing images (RSIs) exhibit extensive spatial coverage and complex geographic backgrounds, where salient objects in the optical RSIs present a variety of scales, shapes, and orientations. Over the past few years, many deep learning-b... read more 

An AI-driven fire risk forecasting framework for urban villages using IGWO-optimized LSTM with incremental learning.

PloS one Jun 2, 2026
Artificial intelligence (AI) is reshaping decision-support systems across multiple domains, including risk management and urban safety. Urban villages, characterized by high population density and informal infrastructure, are particularly vulnerable ... read more 

Integrating network toxicology, machine learning, and single-cell sequencing to reveal the FASN-mediated role of phenolic endocrine disruptors in water in promoting prostate cancer.

PloS one Jun 2, 2026
BACKGROUND: Phenolic endocrine-disrupting chemicals (EDCs) like nonylphenol (NP) and octylphenol (OP) are widespread water pollutants. Their estrogen-like properties are suspected contributors to prostate cancer, but their precise molecular mechanism... read more 

ProtAttn-QuadNet: An attention-based deep learning framework for protein-protein interaction prediction using ProtBERT embeddings.

PloS one Jun 2, 2026
Protein-protein interactions (PPIs) form the backbone of most cellular processes, governing signal transduction, gene regulation, and metabolic control. However, experimental approaches to identifying PPIs remain expensive, laborious, and often incom... read more 

Advanced persistent threat detection through multi-modal behavioral analysis.

PloS one Jun 2, 2026
Advanced Persistent Threats (APTs) represent sophisticated cyberattacks characterized by stealth, persistence, and evasion of traditional detection mechanisms. We observed that APT behaviors during lateral movement and data exfiltration share notable... read more 

Assessment of the accuracy of automated tooth segmentation using different orthodontic platforms and models with a large-scale clinical applicability.

European journal of orthodontics Jun 2, 2026
BACKGROUND/OBJECTIVES: Tooth segmentation remains the most time-consuming task during model preparation for digital orthodontic setup. This study aimed to assess the accuracy of AI-based tooth segmentation tools of four widely used orthodontic platfo... read more 
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