ClinFlow — an interactive application for clinical data mining
Stoicescu, Oana; Ferreira, Eija; Tamminen, Satu; Siirtola, Pekka; Chandra, Gunjan; Veijola, Riitta; Röning, Juha (2021-06-01)
Stoicescu, O., Ferreira, E., Tamminen, S., Siirtola, P., Chandra, G., Veijola, R., & Röning, J. (2021). ClinFlow – An Interactive Application for Clinical Data Mining [BA]. In J. Mantas, L. Stoicu-Tivadar, C. Chronaki, A. Hasman, P. Weber, P. Gallos, M. Crişan-Vida, E. Zoulias, & O. S. Chirila, Public Health and Informatics (Vol. 281, pp. 268–272). IOS Press. https://doi.org/10.3233/SHTI210162
© 2021 European Federation for Medical Informatics (EFMI) and IOS Press. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
https://creativecommons.org/licenses/by-nc/4.0/
https://urn.fi/URN:NBN:fi-fe2021070741217
Tiivistelmä
Abstract
Analyzing clinical data comes with many challenges. Medical expertise combined with statistical and programming knowledge must go hand-in-hand when applying data mining methods on clinical datasets. This work aims at bridging the gap between clinical expertise and computer science knowledge by providing an application for clinical data analysis with no requirement for statistical programming knowledge. Our tool allows clinical researchers to conduct data processing and visualization in an interactive environment, thus providing an assisting tool for clinical studies. The application was experimentally evaluated with an analysis of Type 1 Diabetes clinical data. The results obtained with the tool are in line with the domain literature, demonstrating the value of our application in data exploration and hypothesis testing.
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