Classification of Type-2 Diabetes using Bat-based Fuzzy Rule Miner

2020 ◽  
pp. 79-97
Author(s):  
Ramalingaswamy Cheruku ◽  
Damodar Reddy Edla ◽  
Venkatanareshbabu Kuppili
Keyword(s):  
Type 2 Diabetes ◽  
Fuzzy Rule

Classification of Type-2 Diabetes using Dual-Stage Cascade Network

2020 ◽  
pp. 99-110
Author(s):  
Ramalingaswamy Cheruku ◽  
Damodar Reddy Edla ◽  
Venkatanareshbabu Kuppili
Keyword(s):  
Type 2 Diabetes ◽  
Dual Stage

Classification of Type-2 Diabetes using Spider Monkey Crisp Rule Miner

2020 ◽  
pp. 53-77
Author(s):  
Ramalingaswamy Cheruku ◽  
Damodar Reddy Edla ◽  
Venkatanareshbabu Kuppili
Keyword(s):  
Type 2 Diabetes ◽  
Spider Monkey

scholarly journals Arrhythmic gut microbiome signatures for risk profiling of Type-2 Diabetes

2019 ◽  
Author(s):  
Sandra Reitmeier ◽  
Silke Kießling ◽  
Thomas Clavel ◽  
Markus List ◽  
Eduardo L. Almeida ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Gut Microbiome ◽  
Prediction Models ◽  
Area Under The Curve ◽  
Factors Affecting ◽  
Risk Profiling ◽  
Initial Sampling ◽  
Risk Pattern

SummaryTo combat the epidemic increase in Type-2-Diabetes (T2D), risk factors need to be identified. Diet, lifestyle and the gut microbiome are among the most important factors affecting metabolic health. We demonstrate in 1,976 subjects of a prospective population cohort that specific gut microbiota members show diurnal oscillations in their relative abundance and we identified 13 taxa with disrupted rhythmicity in T2D. Prediction models based on this signature classified T2D with an area under the curve of 73%. BMI as microbiota-independent risk marker further improved diagnostic classification of T2D. The validity of this arrhythmic risk signature to predict T2D was confirmed in 699 KORA subjects five years after initial sampling. Shotgun metagenomic analysis linked 26 pathways associated with xenobiotic, amino acid, fatty acid, and taurine metabolism to the diurnal oscillation of gut bacteria. In summary, we determined a cohort-specific risk pattern of arrhythmic taxa which significantly contributes to the classification and prediction of T2D, highlighting the importance of circadian rhythmicity of the microbiome in targeting metabolic human diseases.

scholarly journals Insomnia is associated with an increased risk of type 2 diabetes in the clinical setting

2018 ◽  
Vol 6 (1) ◽  
pp. e000604 ◽  
Author(s):  
Erin S LeBlanc ◽  
Ning X Smith ◽  
Gregory A Nichols ◽  
Michael J Allison ◽  
Gregory N Clarke
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Clinical Setting ◽  
Clinical Importance ◽  
International Classification Of Diseases ◽  
Hospital Inpatient ◽  
Increased Risk ◽  
Traditional Risk Factors

ObjectiveTo determine the possible association between insomnia and risk of type 2 diabetes mellitus (T2DM) in the naturalistic clinical setting.Research design and methodsWe conducted a retrospective cohort study to examine the risk of developing T2DM among patients with pre-diabetes with and without insomnia. Participants with pre-diabetes (identified by a physician or via two laboratory tests) between January 1, 2007 and December 31, 2015 and without sleep apnea were followed until December 31, 2016. Patients were determined to have T2DM when two of the following occurred within a 2-year window: physician-entered outpatient T2DM diagnosis (International Classification of Diseases [ICD]-9 250.00; ICD-10 E11), dispensing of an antihyperglycemia agent, and hemoglobin A1c (A1c) >6.5% (48 mmol/mol) or fasting plasma glucose (FPG) >125 mg/dL. One hospital inpatient stay with an associated T2DM diagnosis was also sufficient for classification of T2DM.ResultsOur cohort consisted of 81 233 persons with pre-diabetes, 24 146 (29.7%) of whom had insomnia at some point during the 4.3-year average observation period. After adjustment for traditional risk factors, those with insomnia were 28% more likely to develop T2DM than those without insomnia (HR 1.28; 95% CI 1.24 to 1.33). The estimate was essentially unchanged after adjusting for baseline A1c level (HR 1.32; 95% CI 1.25 to 1.40) or FPG (HR 1.28; 95% CI 1.23 to 1.33).ConclusionsInsomnia imparts an increased risk of T2DM comparable with that conferred by traditional risk factors (eg, overweight, non-white race, cardiovascular risk factors). This association could have clinical importance because it suggests a new potentially modifiable risk factor that could be targeted to prevent diabetes.

GAD antibodies in classification of Asian type 2 diabetes

Diabetes Care ◽  
1999 ◽  
Vol 22 (6) ◽  
pp. 1011-1012 ◽  
Author(s):  
M. Fukui ◽  
N. Nakamura ◽  
M. Kondo
Keyword(s):  
Type 2 Diabetes ◽  
Gad Antibodies

scholarly journals Triglyceride-to-HDL Cholesterol Ratio in the Dyslipidemic Classification of Type 2 Diabetes

Diabetes Care ◽  
2005 ◽  
Vol 28 (7) ◽  
pp. 1798-1800 ◽  
Author(s):  
A. M. Wagner ◽  
A. Perez ◽  
J. L. Sanchez-Quesada ◽  
J. Ordonez-Llanos
Keyword(s):  
Type 2 Diabetes ◽  
Hdl Cholesterol ◽  
Cholesterol Ratio

scholarly journals The relationship between periodontite and diabetes mellitus type ii facing the new classification of periodontal diseases: literature review

2020 ◽  
Vol 68 ◽  
Author(s):  
Lívia Maria Lopes de OLIVEIRA ◽  
Lívia Mirelle BARBOSA
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Literature Review ◽  
Periodontal Disease ◽  
Periodontal Diseases ◽  
New Classification ◽  
The Relationship

ABSTRACT Periodontal disease and type 2 diabetes mellitus are considered chronic diseases that at their core have a deep relationship with inflammation. It is assumed that there is a bidirectional relationship between periodontal disease and type 2 diabetes mellitus. It is estimated that approximately 10% of the world’s population is affected by periodontal disease, in its most severe form, almost the same percentage estimated for people with diabetes, which is considered a 21st century emergency. The World Workshop for the Classification of Periodontal and Peri-implant Diseases and Conditions took place from September 9-11, 2017. The aim of this study is to analyze the results of this workshop with regard to the relationship between periodontal diseases/conditions and diabetes mellitus, in addition to conducting an integrative review on the topic. A literature review was conducted, using the Medline electronic databases via Pubmed, Scientific Electronic Library Online, Scientific and Technical Literature of Latin America and the Caribbean and Virtual Health Library. A new classification of periodontal disease included tools for individual assessment of the patient and recognizing risk factors that might negatively interfere in response to treatment. The occurrence of metabolic lack of control in periodontal patients with type 2 diabetes mellitus is now considered a factor of great importance for the assessment of individual susceptibility to the progression of periodontitis. Diabetes is believed to promote a hyper inflammatory response to bacterial challenge by modifying the tissue response of periodontal tissues.

Sign in / Sign up

Export Citation Format

Share Document