Artificial Intelligence Medical Compendium

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 

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 

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 

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 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 

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 

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 

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 

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 

This study examines the global Mittag-Leffler synchronization (GMLS) problem for fractional-order Clifford-valued neural networks (FOCLVNNs) including transmission delays and impulses. Firstly, a novel kind of FOCLVNNs is developed that incorporates ... read more