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Gaining Computational Insight Into Psychological Data: Applications Of Machine Learning With Eating Disorders And Autism Spectrum Disorder, Natalia Rosenfield Aug 2020

Gaining Computational Insight Into Psychological Data: Applications Of Machine Learning With Eating Disorders And Autism Spectrum Disorder, Natalia Rosenfield

Computational and Data Sciences (PhD) Dissertations

Over the past 100 years, assessment tools have been developed that allow us to explore mental and behavioral processes that could not be measured before. However, conventional statistical models used for psychological data are lacking in thoroughness and predictability. This provides a perfect opportunity to use machine learning to study the data in a novel way. In this paper, we present examples of using machine learning techniques with data in three areas: eating disorders, body satisfaction, and Autism Spectrum Disorder (ASD). We explore clustering algorithms as well as virtual reality (VR).

Our first study employs the k-means clustering algorithm to …


Connecting The Dots For People With Autism: A Data-Driven Approach To Designing And Evaluating A Global Filter, Viseth Sean May 2020

Connecting The Dots For People With Autism: A Data-Driven Approach To Designing And Evaluating A Global Filter, Viseth Sean

Computational and Data Sciences (PhD) Dissertations

"Social communication is the use of language in social contexts. It encompasses social interaction, social cognition, pragmatics, and language processing” [3]. One presumed prerequisite of social communication is visual attention–the focus of this work. “Visual attention is a process that directs a tiny fraction of the information arriving at primary visual cortex to high-level centers involved in visual working memory and pattern recognition” [7]. This process involves the integration of two streams: the global and local streams; the global stream rapidly processes the scene, and the local stream processes details. This integration is important to social communication in that attending …


A Behavioral And Voltammetric Study Of The Effects Of Pb Exposure In Mice As A Model Of Autism Spectrum Disorder, Brenna Parke Apr 2020

A Behavioral And Voltammetric Study Of The Effects Of Pb Exposure In Mice As A Model Of Autism Spectrum Disorder, Brenna Parke

Theses and Dissertations

Despite being a known toxin for several centuries, lead (Pb2+) is still utilized in commercial products including leaded gasoline, paint, and modern cosmetics. This presence has caused (Pb2+) to pollute the environment, including public drinking water sources. The recent outbreaks of elevated levels of (Pb2+) in the drinking water in Flint, Michigan and Washington D.C. have caused large populations to be exposed to the heavy metal for months at a time, raising a public health concern over the implications of widespread, long-term (Pb2+) exposure. Young children are most susceptible to the effects …


Wayfinder Application For Autistic Occupational Assistance, Nathaniel Edward Hishon Jan 2020

Wayfinder Application For Autistic Occupational Assistance, Nathaniel Edward Hishon

Master's Theses

Employment among autistic individuals is an area of noted difficulty, with an employment rate well below the general population [1]. Several barriers attributed to autistic unemployment, including difficulties communicating with employers and social interactions with coworkers, obsessive adherence to routine, and trouble organizing and completing workplace tasks, are also attributed to challenges in maintaining employment [2]. Several studies have concluded that long-term employment support is necessary to acquire and maintain autistic employment [3]. The noted benefit of intensive job training, such as access to job coaches, indicates the need for further support to help autistic individuals complete workplace tasks and …


Novel Random Forest Methods And Algorithms For Autism Spectrum Disorders Research, Afrooz Jahedi Jan 2020

Novel Random Forest Methods And Algorithms For Autism Spectrum Disorders Research, Afrooz Jahedi

CGU Theses & Dissertations

Random Forest (RF) is a flexible, easy to use machine learning algorithm that was proposed by Leo Breiman in 2001 for building a predictor ensemble with a set of decision trees that grow in randomly selected subspaces of data. Its superior prediction accuracy has made it the most used algorithms in the machine learning field. In this dissertation, we use the random forest as the main building block for creating a proximity matrix for multivariate matching and diagnostic classification problems that are used for autism research (as an exemplary application). In observational studies, matching is used to optimize the balance …