The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology in the form …

This article describes the design, implementation, and evaluation of an educational mobile
game. Pickstar aims to make vocabulary learning training more accessible to families with …

Sparse nonnegative matrix factorization (SNMF) aims to factorize a data matrix into two
optimized nonnegative sparse factor matrices, which could benefit many tasks, such as …

We describe a novel framework for the discovery of underlying topics of a longitudinal
collection of scholarly data, and the tracking of their lifetime and popularity over time. Unlike …

Entry profiles can be generated before children with Autism Spectrum Disorders (ASD)
begin to traverse an intervention program. They can help evaluate the progress of each child …

Current machine learning algorithms, when directly applied to medical data, often fail to
provide a good understanding of prognosis. This study provides three pathways to make …

Nonnegative Matrix Factorization (NMF) aims to factorize a matrix into two optimized
nonnegative matrices appropriate for the intended applications. The method has been …

The spectrum nature and heterogeneity within autism spectrum disorders (ASD) pose as a
challenge for treatment. Personalisation of syllabus for children with ASD can improve the …

The continuously increasing cost of the US healthcare system has received significant
attention. Central to the ideas aimed at curbing this trend is the use of technology, in the form …

This thesis is the first to address the problems of early intervention in Autism Spectrum
Disorder through the lens of machine learning and data analytics. The key contribution is the …