Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/207659
Authors: 
Loku, Lindita
Fetaji, Bekim
Krstev, Aleksandar
Fetaji, Majlinda
Zdravev, Zoran
Year of Publication: 
2019
Citation: 
[Title:] Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Rovinj, Croatia, 12-14 September 2019 [ISSN:] 2706-4735 [Volume:] 5 [Pages:] 17-24
Abstract: 
The focus of the research study is to investigate and analyses the current data processing and analytics issues in health focusing in diabetes data order to make sense of the data and use it to improve the health system. Within the investigation of the set of data from the ministry of health of Kosovo realised several types of analyses using different software tools. The current main challenge is to efficiently translate science into modern medicine that is limited by our capacity to process and understand these data. So, it is obviously needed to devise new mathematical as well as computational model with the ability to analyse Data. This will help the clinicians to retrieve useful information and then accurately diagnose and treat patients to improve patient outcomes. Scientist as well as medicine workers should become more aware and understand the value of Data analytics in providing valuable insights. Data, derived by patients and consumers, also requires analytics to become actionable. Based on the above results and test of homogeneity we assume that the first group Insuline M will in the future retain higher rate with a standard deviation of .176 compared with the first group Insuline R. This gives as opportunity to predict the management of diabetes for the next years where we can conclude that group 1 will continue to prevail and require more special treatment compared with group 2. Insights are provided as well as arguments and discussed the benefits from the study.
Subjects: 
diabetes
data processing
machine learning
computational model
data analytics
JEL: 
A31
Document Type: 
Conference Paper

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