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Clinflow : an interactive application for processing and exploring clinical data |
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| Author: | Stoicescu, Oana1 |
| Organizations: |
1University of Oulu, Faculty of Information Technology and Electrical Engineering, Department of Computer Science and Engineering, Computer Science |
| Format: | ebook |
| Version: | published version |
| Access: | open |
| Online Access: | PDF Full Text (PDF, 5.4 MB) |
| Pages: | 73 |
| Persistent link: | http://urn.fi/URN:NBN:fi:oulu-202004241542 |
| Language: | English |
| Published: |
Oulu : O. Stoicescu,
2020
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| Publish Date: | 2020-04-24 |
| Thesis type: | Master's thesis |
| Tutor: |
Haapalainen Ferreira, Eija |
| Reviewer: |
Tamminen, Satu Haapalainen Ferreira, Eija |
| Description: |
Abstract Clinical data is the most valuable resource in healthcare development, but it also comes with many challenges. When clinical researchers are required to combine medical expertise with statistical and programming knowledge, the need for data analysis tools arises. The aim of this thesis was to design ClinFlow, an application for clinical data processing and visualization based on user needs. R language and Shiny framework were selected for creating this tool. The goal was to give the means for the clinical researcher to conduct data analysis in an interactive environment, with no need for statistical programming knowledge. A case study using data from The Finnish Type 1 Diabetes Prediction and Prevention (DIPP) study was conducted to demonstrate the feasibility of this application. The initial results achieved in this case study support the previous research of the DIPP study. ClinFlow shows potential for becoming a useful data analysis tool for clinical research. see all
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| Copyright information: |
© Oana Stoicescu, 2020. This publication is copyrighted. You may download, display and print it for your own personal use. Commercial use is prohibited. |