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A GNN-based multi-task learning framework for personalized video search

Watching online videos has become more and more popular and users tend to watch videos based on their personal tastes and preferences. …

Li Zhang, Lei Shi, Jiashu Zhao, Juan Yang, Tianshu Lyu, Dawei Yin, Haiping Lu

Hierarchical clustering split for low-bias evaluation of drug-target interaction prediction

Drug-target interaction (DTI) prediction is important in drug discovery and chemogenomics studies. Machine learning, particularly deep …

Peizhen Bai, Filip Miljković, Yan Ge, Nigel Greene, Bino John, Haiping Lu

Improving Negative Sampling in Graph Neural Networks for Predicting Drug-Drug Interactions

Predicting drug-drug interactions (DDIs) becomes an increasingly important problem in the computational domain, due to the acceleration …

Alexandra Herghelegiu, Haiping Lu

Confidence-quantifying landmark localisation for cardiac MRI

Landmark localisation in medical imaging has achieved great success using deep encoder-decoder style networks to regress heatmap images …

Lawrence Schobs, Shuo Zhou, Marcella Cogliano, Andrew J Swift, Haiping Lu

A feature-importance-aware and robust aggregator for GCN

Neighborhood aggregation is a key step in Graph Convolutional Networks (GCNs) for graph representation learning. Two commonly used …

Li Zhang, Haiping Lu

Geodesically smoothed tensor features for pulmonary hypertension prognosis using the heart and surrounding tissues

Cardiac magnetic resonance imaging (CMRI) provides non-invasive characterization of the heart and surrounding tissues. It is an …

Johanna Uthoff, Samer Alabed, Andrew Swift, Haiping Lu

Side information dependence as a regularizer for analyzing human brain conditions across cognitive experiments

The increasing of public neuroimaging datasets opens a door to analyzing homogeneous human brain conditions across datasets by transfer …

Shuo Zhou, Wenwen Li, Christopher Cox, Haiping Lu

Tri-graph information propagation for polypharmacy side effect prediction

The use of drug combinations often leads to polypharmacy side effects (POSE). A recent method formulates POSE prediction as a link …

Hao Xu, Shengqi Sang, Haiping Lu

Improving whole-brain neural decoding of fMRI with domain adaptation

In neural decoding, there has been a growing interest in machine learning on functional magnetic resonance imaging (fMRI). However, the …

Shuo Zhou, Christopher R Cox, Haiping Lu

Sturm: Sparse tubal-regularized multilinear regression for fMRI

While functional magnetic resonance imaging (fMRI) is important for healthcare/neuroscience applications, it is challenging to classify …

Wenwen Li, Jian Lou, Shuo Zhou, Haiping Lu