1. Research Background and Disciplinary Frontiers Cancer prognosis analysis has always been a core research direction in the medical field. In recent years, with the widespread application of high-throughput sequencing technologies, scientists have been able to delve deeper into exploring molecular biomarkers and clinical characteristics of cancer ...

A New Approach to Emotion Recognition in Conversations Based on Graph Neural Networks Research Background Emotion recognition (ER) is an important component of human-computer interaction (HCI), aiming to identify human emotional states by analyzing multimodal data such as speech, text, and video. This technology has broad application prospects in f...

Title: Generating and Detecting Spatio-Temporal Graph-Based Adversarial False Data Injection Evasion Attacks in Smart Grids Background With the continuous development of modern smart grids, the grid, as a typical Cyber-Physical System (CPS), faces numerous security threats due to the extensive exchange of data between its components. Among these, F...

Representation Learning of Lung Cancer Based on Graph Neural Networks Background Introduction With the rapid development of digital pathology, image-based diagnostic systems are becoming increasingly important in precise pathological diagnosis. These systems rely on Multiple Instance Learning (MIL) technology for Whole Slide Images (WSIs). However,...

Multiple Prior Knowledge Graph Neural Network in Multi-Omics Data Analysis Background Introduction Precision medicine is an important field for the future of healthcare as it provides personalized treatment plans for patients, improving treatment outcomes and reducing costs. For instance, due to the complex clinical, pathological, and molecular cha...