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Description
Engineering an object means engineering the process that creates the object. Today, software can make the task of tracking these processes robust and straightforward. When engineering requirements are strict and strenuous, software custom-built for such processes can prove essential. The work for this project was developing ICDB, an inventory control

Engineering an object means engineering the process that creates the object. Today, software can make the task of tracking these processes robust and straightforward. When engineering requirements are strict and strenuous, software custom-built for such processes can prove essential. The work for this project was developing ICDB, an inventory control and build management system created for spacecraft engineers at ASU to record each step of their engineering processes. In-house development means ICDB is more precisely designed around its users' functionality and cost requirements than most off-the-shelf commercial offerings. By placing a complex relational database behind an intuitive web application, ICDB enables organizations and their users to create and store parts libraries, assembly designs, purchasing and location records for inventory items, and more.
ContributorsNoss, Karl Friederich (Author) / Davulcu, Hasan (Thesis director) / Rios, Ken (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
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Description
Online social networks are the hubs of social activity in cyberspace, and using them to exchange knowledge, experiences, and opinions is common. In this work, an advanced topic modeling framework is designed to analyse complex longitudinal health information from social media with minimal human annotation, and Adverse Drug Events and

Online social networks are the hubs of social activity in cyberspace, and using them to exchange knowledge, experiences, and opinions is common. In this work, an advanced topic modeling framework is designed to analyse complex longitudinal health information from social media with minimal human annotation, and Adverse Drug Events and Reaction (ADR) information is extracted and automatically processed by using a biased topic modeling method. This framework improves and extends existing topic modelling algorithms that incorporate background knowledge. Using this approach, background knowledge such as ADR terms and other biomedical knowledge can be incorporated during the text mining process, with scores which indicate the presence of ADR being generated. A case control study has been performed on a data set of twitter timelines of women that announced their pregnancy, the goals of the study is to compare the ADR risk of medication usage from each medication category during the pregnancy.

In addition, to evaluate the prediction power of this approach, another important aspect of personalized medicine was addressed: the prediction of medication usage through the identification of risk groups. During the prediction process, the health information from Twitter timeline, such as diseases, symptoms, treatments, effects, and etc., is summarized by the topic modelling processes and the summarization results is used for prediction. Dimension reduction and topic similarity measurement are integrated into this framework for timeline classification and prediction. This work could be applied to provide guidelines for FDA drug risk categories. Currently, this process is done based on laboratory results and reported cases.

Finally, a multi-dimensional text data warehouse (MTD) to manage the output from the topic modelling is proposed. Some attempts have been also made to incorporate topic structure (ontology) and the MTD hierarchy. Results demonstrate that proposed methods show promise and this system represents a low-cost approach for drug safety early warning.
ContributorsYang, Jian (Author) / Gonzalez, Graciela (Thesis advisor) / Davulcu, Hasan (Thesis advisor) / Liu, Huan (Committee member) / Papotti, Paolo (Committee member) / Arizona State University (Publisher)
Created2017