An application of predictive model in detecting chronic kidney failure and disease using fuzzy logic / Nur Idrina Zakaria & Ain Nazirah Mohd Adnan
The 24th report of the Malaysian Dialysis and Transplant register for 2016 states that Malaysia has seen 100% increment in the number of new dialysis patients that suffer from chronic kidney disease (CKD) over the past 10 years. Therefore, this research aimed to predict the CKD using fuzzy logic too...
محفوظ في:
| المؤلفون الرئيسيون: | , |
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| التنسيق: | أطروحة |
| اللغة: | English |
| منشور في: |
2019
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| الموضوعات: | |
| الوصول للمادة أونلاين: | https://ir.uitm.edu.my/id/eprint/41362/1/41362.pdf |
| الوسوم: |
إضافة وسم
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| الملخص: | The 24th report of the Malaysian Dialysis and Transplant register for 2016 states that Malaysia has seen 100% increment in the number of new dialysis patients that suffer from chronic kidney disease (CKD) over the past 10 years. Therefore, this research aimed to predict the CKD using fuzzy logic toolbox. The data were collected from seventy clinical test patients based on blood urea nitrogen, eGFR (estimated glomerular filtration rate) and serum creatinine test The fuzzification of these data was generated using fuzzy toolbox in MATLAB software. As a conclusion, early detection of CKD is very important. The result showed the status of CKD for each patient whether a “Yes” or “No”. As a conclusion, early detection of CKD is very important to help patients to be treated at an early stage with the follow-up treatment and consultation with the nephrologist |
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