Dissertation
Healthcare in AI for social good: an examination of applications in social media
Doctor of Philosophy (Ph.D.), Drexel University
Jun 2023
DOI:
https://doi.org/10.17918/00001642
Abstract
AI for social good (AI4SG) is an area of research that is centered around the notion that machine learning (ML) should be used to benefit society. This dissertation will begin by examining different definitions of AI4SG as well as combining them in order to better understand what defines AI research aimed at benefiting society. Since health applications are the most prominent in AI4SG, this dissertation will explore machine learning solutions in healthcare that adhere to AI4SG principles. To increase benefit to society while reducing harm caused by performing research, we will use user generated data from social media and explore why using this data can be beneficial in this type of research. This dissertation will focus on two applications where machine learning is applied to healthcare related user generated data such that it can produce benefit to society. The first application is the use of COVID-19 vaccine related discourse on social media to better understand public concerns about vaccination. Using a combination of topic and sentiment analysis allows us to better understand the themes that emerge in this discourse so that they can be properly addressed. The second application is an online health community for pregnancy after loss support. Using the content from this community allows us to better understand how support flows through a support community of this kind. Additionally, an ML model that combines features from the network structure as well as the detected social support content of messages is used to provide recommendations to users. These two applications demonstrate possible uses for ML in healthcare using user generated data primarily from social media. Through these applications, we will also better understand AI4SG, its advantages and limitations.
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Details
- Title
- Healthcare in AI for social good
- Creators
- Michal Monselise
- Contributors
- Christopher C. Yang (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- viii, 100 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Information Science (Informatics) (2013-2026); College of Computing and Informatics (2013-2026); Drexel University
- Other Identifier
- 991020504815604721