Artificial Intelligence Medical Compendium

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

Showing 72,831 to 72,840 of 235,381 articles

Denoising of high-resolution 3D UTE-MR angiogram data using lightweight and efficient convolutional neural networks.

Magnetic resonance imaging
High-resolution magnetic resonance angiography (∼ 50 μm MRA) data plays a critical role in the accurate diagnosis of various vascular disorders. However, it is very challenging to acquire, and it is susceptible to artifacts and noise which limits its... read more 

Semantic discrete decoder based on adaptive pixel clustering for monocular depth estimation.

Neural networks : the official journal of the International Neural Network Society
Monocular depth estimation (MDE) has long been a popular and challenging task. Currently, mainstream methods mainly include regression methods based on geometric constraints and ordinal regression methods based on discretized depth intervals. However... read more 

Knowledge graph information bottleneck enhanced molecular representation learning.

Neural networks : the official journal of the International Neural Network Society
Effective molecular representation learning (MRL) is essential for advancing molecular property prediction. In recent years, graph-based MRL methods have made significant progress by effectively utilizing the topology structure of molecules. Research... read more 

Multiple-input and multiple-output encoders with DNA-based winner-take-all neural Networks.

Neural networks : the official journal of the International Neural Network Society
DNA logic circuits are essential building blocks for molecular computers. Traditional molecular logic circuits primarily use basic gate circuits as computational units, achieving complex functions via multiple cascades. However, even simple logical f... read more 

3DBench: A scalable benchmark for object and scene-level instruction-tuning of 3D large language models.

Neural networks : the official journal of the International Neural Network Society
Recent assessments of Multi-Modal Large Language Models (MLLMs) have been thorough. However, a detailed benchmark that integrates point cloud data with language for MLLMs remains absent, leading to superficial comparisons that obscure advancements in... read more 

Multi-view graph clustering with Dually Enhanced Tensor Rank Minimization and Diverse Separation of Inconsistent Information.

Neural networks : the official journal of the International Neural Network Society
Multi-view graph clustering is a powerful machine-learning technique for data analysis. However, most of the previous methods still suffer from several limitations. First, most methods overlook the potential inconsistent information in multiple views... read more 

Lyophilized nasal swabs for COVID-19 detection by ATR-FTIR spectroscopy: Machine learning-based approach.

Biophysical chemistry
The COVID-19 pandemic continues to pose challenges for global health. The disease burden and diagnostic pressure has forced scientists to explore alternate diagnostic tools beyond the standard PCR testing. One such promising tool is the use of spectr... read more 

Crosstalk of glutamine metabolism between cancer-associated fibroblasts and cancer cells.

Cellular signalling
Glutamine (Gln), a critical metabolic substrate, fuels the uncontrolled proliferation of cancer cells. Cancer-associated fibroblasts (CAFs), essential components of the tumor microenvironment, facilitate tumor progression by supplying Gln to cancer c... read more 

Memory Transmission Based Referring Video Object Segmentation.

Neural networks : the official journal of the International Neural Network Society
Referring Video Object Segmentation (RVOS) addresses the task of segmenting target objects described by textual descriptions from videos. In order to ensure the consistency of objects segmented from video frames, inter-frame modeling is adopted to ca... read more 

Rethinking cell-based neural architecture search: A theoretical perspective.

Neural networks : the official journal of the International Neural Network Society
In this paper, we explore several fundamental theoretical issues in cell-based neural architecture search, including whether different architectures in search space are equally important in terms of the minimal training loss they can achieve, and whe... read more