A5036629858- Topic Modeling
- Advanced Graph Neural Networks
- Semantic Web and Ontologies
- Data Quality and Management
- Natural Language Processing Techniques
- Cardiovascular Disease and Adiposity
- Advanced Image and Video Retrieval Techniques
- Cardiovascular Function and Risk Factors
- Web Data Mining and Analysis
- Cardiac Imaging and Diagnostics
- Recommender Systems and Techniques
Jinan University
2025
Nanjing University
2021-2024
Patients with complex coronary artery disease (CAD) often have poor clinical outcomes. This study aimed to develop a predictive model for assessing the 1-year risk of major adverse cardiovascular events (MACE) in patients stable CAD, using retrospective data collected from January 2020 September 2023 at Guangzhou Red Cross Hospital. The goal was enable early stratification and intervention improve A total 369 were included randomly divided into training set (70%) development validation (30%)...
Abstract Nowadays, with increasing open knowledge graphs (KGs) being published on the Web, users depend data portals and search engines to find KGs. However, existing systems provide services present results only metadata while ignoring contents of KGs, i.e., triples. It brings difficulty for users' comprehension relevance judgement. To overcome limitation metadata, in this paper we propose a content-based engine KGs named CKGSE. Our system provides keyword search, KG snippet generation,...
The utilization of semantic information is an important research problem in the field recommender systems, which aims to complement missing parts mainstream ID-based approaches. With rise LLM, its ability act as a knowledge base and reasoning capability have opened up new possibilities for this area, making LLM-based recommendation emerging direction. However, directly using LLM process scenarios unreliable sub-optimal due several problems such hallucination. A promising way cope with use...
Ad hoc dataset retrieval has become an important way of finding data on the Web, where underlying problem is how to measure relevance a query. State-of-the-art solutions for this task are still lexical methods, which cannot capture semantic similarity. Semantics-aware knowledge-enhanced achieved promising results other tasks, have yet be systematically studied specialized task. To fill gap, in paper, we present empirical investigation implement and evaluate, two test collections, set...