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Outputs (130)

Social influence prediction with train and test time augmentation for graph neural networks (2021)
Presentation / Conference Contribution

Data augmentation has been widely used in machine learning for natural language processing and computer vision tasks to improve model performance. However, little research has studied data augmentation on graph neural networks, particularly using aug... Read More about Social influence prediction with train and test time augmentation for graph neural networks.

Investigating Browne's method (2021)
Presentation / Conference Contribution

Results supports Browne’s procedure of pilot sample size determination. However the data reveals that the procedure underestimates and overestimates sample size. Fig. 1 shows 𝛼 and 𝛽 have no practical effect on degree of excess which increases as... Read More about Investigating Browne's method.

Prediction of bladder cancer treatment side effects using an ontology-based reasoning for enhanced patient health safety (2021)
Journal Article

Predicting potential cancer treatment side effects at time of prescription could decrease potential health risks and achieve better patient satisfaction. This paper presents a new approach, founded on evidence-based medical knowledge, using as much i... Read More about Prediction of bladder cancer treatment side effects using an ontology-based reasoning for enhanced patient health safety.