Search Results for author: Paula L. McClean

Found 2 papers, 0 papers with code

Predicting feature imputability in the absence of ground truth

no code implementations14 Jul 2020 Niamh McCombe, Xuemei Ding, Girijesh Prasad, David P. Finn, Stephen Todd, Paula L. McClean, KongFatt Wong-Lin

Data imputation is the most popular method of dealing with missing values, but in most real life applications, large missing data can occur and it is difficult or impossible to evaluate whether data has been imputed accurately (lack of ground truth).

Imputation

Opportunities for multiscale computational modelling of serotonergic drug effects in Alzheimer's disease

no code implementations5 May 2020 Alok Joshi, Da-Hui Wang, Steven Watterson, Paula L. McClean, Chandan K. Behera, Trevor Sharp, KongFatt Wong-Lin

Alzheimer's disease (AD) is an age-specific neurodegenerative disease that compromises cognitive functioning and impacts the quality of life of an individual.

HTR

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