Liang Zhao

DynGraph2Seq: Dynamic-Graph-to-Sequence Interpretable Learning for Health Stage Prediction in Online Health Forums

2019 · arXiv (Cornell University)

Online health communities such as the online breast cancer forum enable patients (i.e., users) to interact and help each other within various subforums, which are subsections of the main forum devoted to specific health topics. …

CBOWRA: A Representation Learning Approach for Medication Anomaly Detection

2019

Electronic health record is an important source for clinical researches and applications, and errors inevitably occur in the data, which lead to severe damages to both patients and hospital services. One of such errors is …

Novel Online Sequential Learning-Based Adaptive Routing for Edge Software-Defined Vehicular Networks

2020 · IEEE Transactions on Wireless Communications

To provide efficient networking services at the edge of Internet-of-Vehicles (IoV), Software-Defined Vehicular Network (SDVN) has been a promising technology to enable intelligent data exchange without giving additional duties to the resource constrained vehicles. Compared …

Graph Neural Networks: Foundation, Frontiers and Applications

2022 · Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the recent years. Graph neural networks, also known as deep learning on graphs, graph representation learning, or geometric deep learning, have …

Privacy-Enhancing Technologies in Federated Learning for the Internet of Healthcare Things: A Survey

2023 · arXiv (Cornell University)

Advancements in wearable medical devices in IoT technology are shaping the modern healthcare system. With the emergence of the Internet of Healthcare Things (IoHT), we are witnessing how efficient healthcare services are provided to patients …

Federated Learning Meets Blockchain in Decentralized Data Sharing: Healthcare Use Case

2024 · IEEE Internet of Things Journal

In the era of data-driven healthcare, the amalgamation of blockchain and Federated Learning (FL) introduces a paradigm shift towards secure, collaborative, and patient-centric data-sharing. This paper pioneers the exploration of the conceptual framework and technical …

Distilling Large Language Models for Text-Attributed Graph Learning

2024 · arXiv (Cornell University)

Text-Attributed Graphs (TAGs) are graphs of connected textual documents. Graph models can efficiently learn TAGs, but their training heavily relies on human-annotated labels, which are scarce or even unavailable in many applications. Large language models …

CSF-GAN: Cross-modal Semantic Fusion-based Generative Adversarial Network for Text-guided Image Inpainting

2024

Most visual-guided image inpainting methods based on generative adversarial networks (GANs) struggle when the missing region has weak correlations with the surrounding visual context. Recently, diffusion-based methods guided by textual context have been proposed to …