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.
OBJECTIVES: Neural networks are a powerful statistical tool that use nonlinear regression type models to obtain predictions. Their use in the Lifeways cross-generation study that examined body mass index (BMI) of children, among other measures, is ex...
Food research international (Ottawa, Ont.)
Dec 5, 2018
Serum free fatty acids (FFA) are generally elevated in obesity. The gut microbiota is involved in the host energy metabolism through the regulation of body fat storage, and a link between diet, FFA and the intestinal microbiota seems to exist. Our ai...
Medical & biological engineering & computing
Nov 26, 2018
Colorectal cancer (CRC) is a common cancer responsible for approximately 600,000 deaths per year worldwide. Thus, it is very important to find the related factors and detect the cancer accurately. However, timely and accurate prediction of the diseas...
AIMS: Non-Caucasian migrants require dedicated approaches in diabetes management due to specific genetic; socio-cultural; demographic and anthropological determinants. Documenting such phenotypes allows for better understanding unmet needs and manage...
BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases. Machine learning techniques were introduced to evaluate the optimal predictive clinical model of NAFLD.
BACKGROUND: While there is increasing interest in identifying pregnancies at risk for adverse outcome, existing prediction models have not adequately assessed population-based risks, and have been based on conventional regression methods. The objecti...
BACKGROUND: Dry weight is the lowest weight patients on hemodialysis can tolerate; correct dry weight estimation is necessary to minimize morbi-mortality, but is difficult to achieve. Here, we used artificial intelligence to improve the accuracy of d...