The utilization of the C50 algorithm in order to identify the influential factors diabetes in women
Diabetes is known as a non-communicable disease, but it is one of the deadliest diseases because the number of diabetic patients continues to increase every year. In general, diabetes is divided into two types, namely type 1 diabetes (autoimmune) and type 2 diabetes (melitus). Research also shows th...
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| description | Diabetes is known as a non-communicable disease, but it is one of the deadliest diseases because the number of diabetic patients continues to increase every year. In general, diabetes is divided into two types, namely type 1 diabetes (autoimmune) and type 2 diabetes (melitus). Research also shows that there is a type of diabetes that can be completely cured and is only found in pregnant women called gestational. However, in pregnant women the symptoms are different and there are several accompanying risk factors. This study built a model with C50 algorithm and indicate the most influential variable which affecting diabetes in women. The research process began with pre-processing the data. After the data was ready for use, the next step was to diagnose diabetes using the C50 algorithm. The diagnostic model built using the C50 algorithm shows an accuracy value of 81.5%. Furthermore, five variables that affect diabetic patients consist of glucose levels, body mass index, pregnancy history, family history of diabetes, and insulin levels. |
| doi_str_mv | 10.1063/5.0120268 |
| format | Conference Proceeding |
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In general, diabetes is divided into two types, namely type 1 diabetes (autoimmune) and type 2 diabetes (melitus). Research also shows that there is a type of diabetes that can be completely cured and is only found in pregnant women called gestational. However, in pregnant women the symptoms are different and there are several accompanying risk factors. This study built a model with C50 algorithm and indicate the most influential variable which affecting diabetes in women. The research process began with pre-processing the data. After the data was ready for use, the next step was to diagnose diabetes using the C50 algorithm. The diagnostic model built using the C50 algorithm shows an accuracy value of 81.5%. 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| fulltext | fulltext |
| identifier | ISSN: 0094-243X |
| ispartof | AIP conference proceedings, 2023, Vol.2706 (1) |
| issn | 0094-243X 1551-7616 |
| language | eng |
| recordid | cdi_scitation_primary_10_1063_5_0120268 |
| source | AIP Journals Complete |
| subjects | Algorithms Body size Diabetes Pregnancy Signs and symptoms Womens health |
| title | The utilization of the C50 algorithm in order to identify the influential factors diabetes in women |
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