Unifying Large Language Models and Knowledge Graphs: A Roadmap

Information Science, Computer Science, Artificial Intelligence,
large language models   knowledge graphs   natural language processing   generative pre-training   bidirectional reasoning   artificial intelligence  

Unified Large Language Models and Knowledge Graphs Background In recent years, numerous research achievements have emerged in the fields of natural language processing and artificial intelligence. Notably, large language models (LLMs) such as ChatGPT and GPT-4 have demonstrated remarkable performance. However, despite their excellent generalization...

Deep Relational Graph Infomax for Knowledge Graph Completion

Information Science, Computer Science, Artificial Intelligence,
knowledge graph embedding   mutual information maximization   graph attention networks   knowledge graph completion   artificial intelligence  

Knowledge Graph (KG) embedding technology is an important research topic in the field of artificial intelligence, mainly used for knowledge acquisition and extension of knowledge graphs. In recent years, although many graph embedding methods have been proposed, these methods typically focus only on the semantic information of the knowledge graph, i...

Artificial Intelligence-Based Classification of Breast Lesion from Contrast Enhanced Mammography: A Multicenter Study

Information Science, Artificial Intelligence, Medicine, Medical Laboratory Science, Medical Imaging, Oncology,
breast lesions   artificial intelligence   diagnosis   mammography   deep learning  

Multi-center Study on Artificial Intelligence-based Classification of Breast Lesions In the field of breast cancer, early diagnosis is crucial for improving treatment efficacy and survival rate. Breast cancer can be mainly divided into two categories: in situ carcinoma and invasive carcinoma, which have significant differences in treatment strategi...

Radiomics-based Prediction of Local Control in Patients with Brain Metastases Following Postoperative Stereotactic Radiotherapy

Information Science, Artificial Intelligence, Medicine, Neurology, Neurosurgery, Medical Imaging, Oncology,
radiomics   machine learning   local failure prediction   brain metastases   artificial intelligence  

Application of Radiomics in Predicting Local Control in Postoperative Stereotactic Radiotherapy for Brain Metastasis Patients Academic Background Brain Metastases (BMs) are the most common malignant brain tumors, far surpassing primary brain tumors like gliomas in incidence. Recent medical guidelines recommend surgical treatment for patients with s...

A Novel CNN-Based Image Segmentation Pipeline for Individualized Feline Spinal Cord Stimulation Modeling

Information Science, Artificial Intelligence, Medicine, Neurology, Medical Imaging, Life Sciences, Bioengineering,
spinal cord stimulation   machine learning   automatic segmentation   axonal recruitment   convolutional neural network   artificial intelligence  

Automated Spinal Cord Segmentation Pipeline Based on Convolutional Neural Network (CNN) for Individualized Cat Spinal Cord Stimulation Modeling Background and Research Motivation Spinal cord stimulation (SCS) is a widely used treatment method for chronic pain management. In recent years, it has also been used to modulate neural activity, aiming to ...

Strokeclassifier: Ischemic Stroke Etiology Classification by Ensemble Consensus Modeling Using Electronic Health Records

Information Science, Artificial Intelligence, Medicine, Environmental and Public Health, Neurology,
stroke   machine learning   artificial intelligence   etiology classification   health records   diagnostic accuracy   secondary prevention  

StrokeClassifier: An AI Tool for Etiological Classification of Ischemic Stroke Based on Electronic Health Records Project Background and Motivation Identifying the etiology of strokes, particularly acute ischemic stroke (AIS), is crucial for secondary prevention, but it is often very challenging. In the United States, there are nearly 676,000 new c...