Technical report: mathematical modelling for detecting diabetes / Nurul Hawanis Saharin, Safiah Nadirah Abdul Halim and Nur Miza Syaheera Ghazali
This paper works to formulate the blood glucose level of diabetes. Diabetes is a syndrome of disorder metabolism which due to combination of hereditary and environmental causes. Thus, its resulting in abnormally high blood sugar level. The two most common of diabetes are due to dependent of insulin...
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| Main Authors: | , , |
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| Format: | Student Project |
| Language: | English |
| Published: |
2017
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/109740/1/109740.pdf https://ir.uitm.edu.my/id/eprint/109740/ |
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| Summary: | This paper works to formulate the blood glucose level of diabetes. Diabetes is a syndrome of disorder metabolism which due to combination of hereditary and environmental causes. Thus, its resulting in abnormally high blood sugar level. The two most common of diabetes are due to dependent of insulin (Type 1) and independent of insulin (type 2). It will be explained how the hormones and insulin activated and how its effect glucose level in blood. In this research proposed a mathematical model for the study of diabetes which the subjects based in the results on the glucose tolerance test (GTT) of four to five hours. The model of interaction between glucose and insulin concentration in the body will be formulated and solved. Then, the parameter values can be obtained and substituted into general model to obtain the new predicted glucose concentration. Next, the best fit model for detecting diabetes can be determined. Hence, an indicator will be used which similar to the one that proposed by Osborne (2013) to diagnose a diabetic condition. There are three subjects that will be observed and the data of glucose concentration for each subjects are obtained based on GTT to check the accuracy of the model. As a result, Subject A is the best fit model while Subject C is the good model for detecting diabetes. Then, Subject B is not a good model to detect diabetes. In conclusion, the case of Subject B shows that the model can only be used for mild diabetes or pre-diabetes. |
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