2023 Summer Experience Program Abstracts

https://openworks.mdanderson.org/sumexp23/1130/thumbnail.jp

Transactions of 2019 International Conference on Health Information Technology Advancement Vol. 4 No. 1

The Fourth International Conference on Health Information Technology Advancement Kalamazoo, Michigan, October 31 - Nov. 1, 2019. Conference Co-Chairs Bernard T. Han and Muhammad Razi, Department of Business Information Systems, Haworth College of Business, Western Michigan University Kalamazoo, MI 49008 Transaction Editor Dr. Huei Lee, Professor, Department of Computer Information Systems, Eastern Michigan University Ypsilanti, MI 48197 Volume 4, No. 1 Hosted by The Center for Health Information Technology Advancement, WM

Addiction in context

The dissertation provides a comprehensive exploration of the interplay between social and cultural factors in substance use, specifically focusing on alcohol use disorder (AUD) and cannabis use disorder (CUD). It begins by introducing the concept of social plasticity, which posits that adolescents' susceptibility to AUD is influenced by their heightened sensitivity to their social environment, but this sensitivity increases the potential for recovery in the transition to adulthood.A series of studies delves into how social cues impact alcohol craving and consumption. One study using functional magnetic resonance imaging (fMRI) investigated social alcohol cue reactivity and its relationship to social drinking behavior, revealing increased craving but no significant change in brain activity in response to alcohol cues. Another fMRI study compared social processes in alcohol cue reactivity between adults and adolescents, showing age-related differences in how social attunement affects drinking behavior. Shifting focus to cannabis, this dissertation discusses how cultural factors, including norms, legal policies, and attitudes, influence cannabis use and processes underlying CUD. The research presented examined various facets of cannabis use, including how cannabinoid concentrations in hair correlate with self-reported use, the effects of cannabis and cigarette co-use on brain reactivity, and cross-cultural differences in CUD between Amsterdam and Texas. Furthermore, the evidence for the relationship between cannabis use, CUD, and mood disorders is reviewed, suggesting a bidirectional relationship, with cannabis use potentially preceding the onset of bipolar disorder and contributing to the development and worse prognosis of mood disorders and mood disorders leading to more cannabis use

Excellentia Eminentia Effectio

"In these pages you will learn about the fascinating research endeavors that each of our faculty members is undertaking. We have divided their research into the broad categories of health, sustainability, information, and systems. While we recognize the imperfect nature of categorizing research that, by its very nature may be interdisciplinary or transdisciplinary, we nonetheless believe it will be helpful as a way to see the depth and breadth of our research endeavors within each grouping. As you read the profiles on these pages, I know you will begin to appreciate that, taken as a whole, the research spectrum at Columbia Engineering is exceptional and that, as our professors go about their work, they are at the cusp of making breakthroughs that will have a major impact on the way we live our lives today and tomorrow.

Analysis and Decision-Making with Social Media

abstract: The rapid advancements of technology have greatly extended the ubiquitous nature of smartphones acting as a gateway to numerous social media applications. This brings an immense convenience to the users of these applications wishing to stay connected to other individuals through sharing their statuses, posting their opinions, experiences, suggestions, etc on online social networks (OSNs). Exploring and analyzing this data has a great potential to enable deep and fine-grained insights into the behavior, emotions, and language of individuals in a society. This proposed dissertation focuses on utilizing these online social footprints to research two main threads – 1) Analysis: to study the behavior of individuals online (content analysis) and 2) Synthesis: to build models that influence the behavior of individuals offline (incomplete action models for decision-making). A large percentage of posts shared online are in an unrestricted natural language format that is meant for human consumption. One of the demanding problems in this context is to leverage and develop approaches to automatically extract important insights from this incessant massive data pool. Efforts in this direction emphasize mining or extracting the wealth of latent information in the data from multiple OSNs independently. The first thread of this dissertation focuses on analytics to investigate the differentiated content-sharing behavior of individuals. The second thread of this dissertation attempts to build decision-making systems using social media data. The results of the proposed dissertation emphasize the importance of considering multiple data types while interpreting the content shared on OSNs. They highlight the unique ways in which the data and the extracted patterns from text-based platforms or visual-based platforms complement and contrast in terms of their content. The proposed research demonstrated that, in many ways, the results obtained by focusing on either only text or only visual elements of content shared online could lead to biased insights. On the other hand, it also shows the power of a sequential set of patterns that have some sort of precedence relationships and collaboration between humans and automated planners.Dissertation/ThesisDoctoral Dissertation Computer Science 201

Developing an integrated MDT service model for the management of patients with lung cancer

The motivation for this research was the publication in 1995 of the Calman-Hine report. This provided a strategic framework for the delivery of cancer care by creating a network of cancer care centres in England and Wales to enable patients to receive a uniformly high standard of care. The report acknowledged the fact that although the evidence on optimal cancer care used to prepare the report was based on two key sources (i) medical literature and (ii) audit data provided by UK cancer registries, they did not lend themselves to controlled experiments as most information came from retrospective analyses; hence they were subject to a number of possible flaws and biases. Yet the report recommended some key structural changes to be implemented. The focus of the research described in this thesis was centred on the recommendation of a multidisciplinary team (MDT) review of patients prior to a treatment decision, both in general cancer units as well as in specialised cancer centres. Given the mandate to implement these recommendations, the research questions addressed were “can the current configuration support this recommendation?”, “what evidence was there to support the effectiveness of the MDT?” and “was there a model of care to support the service delivery of cancer care?” A literature review established that there was no existing template upon which MDT services could be set up. This research therefore set out to develop an MDT model to support operational delivery of care in the setting of a cancer centre. The clinical specialty in which this research was undertaken was that of lung cancer. The research successfully developed a conceptual model. However, in the process, a number of operational and practical constraints were identified within the revised service configuration designed to deliver high quality cancer care through the incorporation of the MDT service, and this ultimately limited the extent to which the model could be deployed in the particular clinical setting. Nevertheless, the modelling process did enable a range of core issues to be identified, enabling design solutions to be formulated and tested, thereby confirming the effectiveness of the MDT model. In particular, the adoption of a soft modelling approach was shown to be beneficial in addressing operational problems. By engaging clinical and other end-users right from the start in the modelling process, the models did become operationally accepted, allowing resistance to change to be overcome and the solution to be integrated into the business process. MDT services are now well established, both in cancer units and cancer centres and published data on their effectiveness in the treatment of lung cancer, although not conclusive; demonstrate an increase in resection rates. However, assessing the long-term impact of MDTs on lung cancer outcomes remains a topic for future research