Full metadata
Title
An Introduction to Unstructured Case Management
Description
In the age of information, collecting and processing large amounts of data is an integral part of running a business. From training artificial intelligence to driving decision making, the applications of data are far-reaching. However, it is difficult to process many types of data; namely, unstructured data. Unstructured data is “information that either does not have a predefined data model or is not organized in a pre-defined manner” (Balducci & Marinova 2018). Such data are difficult to put into spreadsheets and relational databases due to their lack of numeric values and often come in the form of text fields written by the consumers (Wolff, R. 2020). The goal of this project is to help in the development of a machine learning model to aid CommonSpirit Health and ServiceNow, hence why this approach using unstructured data was selected. This paper provides a general overview of the process of unstructured data management and explores some existing implementations and their efficacy. It will then discuss our approach to converting unstructured cases into usable data that were used to develop an artificial intelligence model which is estimated to be worth $400,000 and save CommonSpirit Health $1,200,000 in organizational impact.
Date Created
2022-05
Contributors
- Bergsagel, Matteo (Author)
- De Waard, Jan (Co-author)
- Chavez-Echeagaray, Maria Elena (Thesis director)
- Burns, Christopher (Committee member)
- Barrett, The Honors College (Contributor)
- School of Mathematical and Statistical Sciences (Contributor)
- Computer Science and Engineering Program (Contributor)
Topical Subject
Resource Type
Copyright Statement
In Copyright
Primary Member of
Peer-reviewed
No
Open Access
No
Series
Academic Year 2021-2022
Handle
https://hdl.handle.net/2286/R.2.N.166246
System Created
- 2022-05-07 06:09:09
System Modified
- 2023-01-10 11:47:14
- 1 year 10 months ago
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