Investigating Useful Features for Overall Survival Prediction in Patients with Low-Grade Glioma Using Histology Slides

Information Science, Computer Science, Medicine, Medical Laboratory Science,
glioma   low-grade glioma   deep learning   histology   image processing   machine learning  

Useful Features for Overall Survival Prediction in Low-Grade Glioma Patients Academic Background Glioma is a type of neoplastic growth in the brain that usually poses a serious threat to the patients’ lives. In most cases, glioma eventually leads to the death of the patient. The analysis of glioma typically involves examining pathological slices of...

Improving the Segmentation of Pediatric Low-Grade Gliomas through Multitask Learning

Information Science, Artificial Intelligence, Medicine, Pediatrics, Medical Imaging, Oncology,
multitask learning   pediatric low-grade gliomas   MRI   tumor segmentation   deep learning  

Improved Segmentation of Pediatric Low-Grade Gliomas Through Multitask Learning Background Introduction The segmentation of pediatric brain tumors is a critical task in tumor volume analysis and artificial intelligence algorithms. However, this process is time-consuming and requires the expertise of neuroradiologists. Although significant research ...

Deep-Learning-Based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging

Information Science, Electronic Information, Automation, Artificial Intelligence, Medicine, Neurology, Medical Imaging,
deep learning   motor imagery EEG   cortical source imaging   brain functional connectivity   spatiotemporal features   graph convolutional network  

Deep-learning-based Motor Imagery EEG Classification by Exploiting the Functional Connectivity of Cortical Source Imaging Research Background and Motivation A brain-computer interface (BCI) is a system that directly decodes and outputs brain activity information without relying on related neural pathways and muscles, thereby achieving communication...

AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment Enabled by Large Language Models

Information Science, Computer Science, Artificial Intelligence,
entity alignment   knowledge graph   large language model   automatic alignment   predicate proximity graph   deep learning   representation learning  

AutoAlign: A Fully Automated and Efficient Knowledge Graph Alignment Method Driven by Large Language Models Knowledge Graphs (KG) have been widely applied in fields such as question-answering systems, dialogue systems, and recommendation systems. However, different Knowledge Graphs often store the same real-world entities in various forms, leading ...

Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing

Deep Graph Memory Networks for Forgetting-Robust Knowledge Tracing

Information Science, Computer Science, Artificial Intelligence,
forgetting behaviors   knowledge tracing   deep learning   graph memory networks   dynamic knowledge states  

Deep Graph Memory Network for Forgetting-Robust Knowledge Tracing In recent years, Knowledge Tracing (KT) has attracted widespread attention as an important method for personalized learning. The goal of KT is to predict the accuracy of a student’s answers to new questions by utilizing their past answer history to estimate their knowledge state. How...