IEEE journal of biomedical and health informatics
May 20, 2019
We consider the problem in precision health of grouping people into subpopulations based on their degree of vulnerability to a risk factor. These subpopulations cannot be discovered with traditional clustering techniques because their quality is eval...
BACKGROUND: Waist circumference (WC) and z scores of body mass index (BMI) are commonly used to predict childhood obesity, although BMI and WC have a limited sensitivity.
PURPOSE: To estimate prevalence and severity of diabetic retinopathy (DR) among U.S. adults with diabetes and with or without chronic kidney disease (CKD), and assess associated risk of mortality.
Obesity reviews : an official journal of the International Association for the Study of Obesity
Feb 9, 2018
Rich sources of obesity-related data arising from sensors, smartphone apps, electronic medical health records and insurance data can bring new insights for understanding, preventing and treating obesity. For such large datasets, machine learning prov...
OBJECTIVE: To determine the prevalence and possible factors associated with anaemia, and vitamin B and folate deficiencies in women of reproductive age (WRA) in Pakistan.
BACKGROUND: Of the machine learning techniques used in predicting coronary heart disease (CHD), neural network (NN) is popularly used to improve performance accuracy.
American journal of health promotion : AJHP
Dec 22, 2016
PURPOSE: Limited research has evaluated the independent and additive associations of moderate-to-vigorous physical activity (MVPA), sedentary behavior (SB), and cardiorespiratory fitness (CRF) with metabolic syndrome, which was the purpose of this st...
BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research w...
BACKGROUND: Knee osteoarthritis (OA) is the most common joint disease of adults worldwide. Since the treatments for advanced radiographic knee OA are limited, clinicians face a significant challenge of identifying patients who are at high risk of OA ...
BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took acco...
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