Sistem Pendukung Keputusan Untuk Mendeteksi Penyakit Diabetes Melitus Tipe 2 Menggunakan Metode Learning Vector Quantization (LVQ)

ABSTRACT Diabetes is a chronic disease that occurs when the pancreas does not produce enough insulin, or when the body can not effectively use the insulin that is produced. Diabetes mellitus can be divided into two types: Type 1 diabetes mellitus and diabetes mellitus type 2. This study aims to detect diabetes mellitus and may predict the development status (Metabolic Syndrome) using Learning Vector Quantization. The data needed to detect type 2 diabetes are blood sugar levels, genetics, age, physical activity, diet, smoking habits, body mass index, gender and abdominal circumference. In addition, the data also used HbA1C and cholesterol levels to detect the status of the development of type 2 diabetes mellitus (Metabolic Syndrome). The classification process is divided into two stages: stage 1 to determine the type 2 diabetes or Non diabetes mellitus, and phase 2 to predict the prognosis of type 2 diabetes into Metabolic Syndrome or Non Metabolic Syndrome (the patient is still in the category of type 2 diabetes) performed on 200 data respectively divided into 80 training data and 120 testing data. Best detection results at stage 1 that is equal to 96.67% can be obtained using learning rate (α) of 0.7, and the rate of decrement (decα) of 0.75.While the best detection results at stage 2 average accuracy rate of 92.5% using a variety of learning rate (α) and the rate of decrement (decα). Error detection in stage 2 occurs only in the Metabolic Syndrome data detected as Type 2 diabetes mellitus. Keywords : Accuracy, Diabetes Mellitus, Learning Vector Quantization

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Association between +45T>G adiponectin polymorphism gene and type 2 diabetes mellitus and metabolic syndrome in a Venezuelan population

F1000Research ◽

10.12688/f1000research.16890.1 ◽

2019 ◽

Vol 8 ◽

pp. 292

Author(s):

María Patricia Sánchez ◽

Carem Prieto ◽

Endrina Mujica ◽

Kendry Vergara ◽

Enifer Valencia ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Metabolic Syndrome ◽

Type 2 Diabetes Mellitus ◽

Plasma Concentrations ◽

Abdominal Circumference ◽

Control Group ◽

Polymorphism Analysis ◽

Mean Values

Background: Adiponectin (ADIPOQ) is a hormone primarily synthesized by adipocytes and encoded by the ADIPOQ gene, which exerts anti-inflammatory, antiatheratogenic and insulin sensitizing functions. It has been shown that its plasma concentrations are decreased in individuals with metabolic syndrome (MS) and type 2 diabetes mellitus (DM2), which could be due to variations in the gene coding for this protein. The aim of this study was to detect the +45 T>G polymorphism of the ADIPOQ gene in subjects with DM2 and MS in Maracaibo municipality, Zulia state, Venezuela. Methods: A total of 90 subjects who attended the Center for Metabolic Endocrine Research "Dr. Félix Gómez" were enrolled for this study, 46 of which had MS-DM2 and 44 of which were healthy control individuals. Genomic DNA was extracted from blood samples and PCR-restriction fragment length polymorphism analysis was carried out for the promoter region of the ADIPOQ gene. Likewise, the +45 T> G polymorphism was identified and correlated with MS and DM2 in the studied population. Results: The most frequent allele in both groups was the T allele, and the predominant genotype was homozygous T/T (79%). Genotypes with heterozygous T/G and G/G homozygous polymorphism were more frequent in the control group than in the MS-DM2 group. Regarding the individuals with T/G and G/G genotypes, statistically significant lower mean values were found for fasting glucose, total cholesterol, triacylglycerides, abdominal circumference, and for the medians of systolic and diastolic blood pressure. Odds ratio were calculated for the presence or absence of MS and DM2. Conclusions: The results suggested that the presence of the G allele exerts a protective effect on the carrier individuals, thus avoiding the appearance of the aforementioned metabolic alterations.

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