Comput. Biol. Med. - Exploring the effects of intervention for those at high risk of developing type 2 diabetes using a computer simulation.

Tópicos

{ risk(3053) factor(974) diseas(938) }
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{ featur(3375) classif(2383) classifi(1994) }
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Resumo

A simulation based computational method was conducted to reflect the effect of intervention for those at high risk of type 2 diabetes. Hierarchy Support Vector Machines (H-SVMs) were used to classify high risk. The proportion transitioning from the high risk state to moderate state, low state or the normal state was calculated. When Body Mass Index (BMI) decreased by 5% (weight loss 3-5kg), the proportion of Class A transferring to a lower state was 15-25%, and risk also appeared reduced for Class B1. In Class C, when cholesterol (CHOL) was decreased by 2.5% (0.13-0.34mmol/L), 10-25% transitioned to a lower risk state. The method could help determine risk transition by the adjustment of sensitive risk factors. This might provide the basis for implementing intervention in cases in a high risk state.

Resumo Limpo

simul base comput method conduct reflect effect intervent high risk type diabet hierarchi support vector machin hsvms use classifi high risk proport transit high risk state moder state low state normal state calcul bodi mass index bmi decreas weight loss kg proport class transfer lower state risk also appear reduc class b class c cholesterol chol decreas mmoll transit lower risk state method help determin risk transit adjust sensit risk factor might provid basi implement intervent case high risk state

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