Data mining involves the use of mathematical sciences, statistics, artificial intelligence, and
machine learning to determine the relationships between variables from a large sample of …

Machine learning is a class of algorithms able to handle a large number of predictors with
potentially nonlinear relationships. By applying machine learning to obesity, researchers …

Obesity is strongly associated with multiple risk factors. It is significantly contributing to an
increased risk of chronic disease morbidity and mortality worldwide. There are various …

The increased prevalence of childhood obesity is expected to translate in the near future into
a concomitant soaring of multiple cardio-metabolic diseases. Obesity has a complex …

Childhood and adolescent obesity is a serious health problem that is on the rise at the
global level. Earlier, certain diseases such as Type 2 diabetes, high blood pressure, and …

Due to digital transformation, an autonomous vehi-cle (AV) is realized as a network of
multiple electronic control units (ECUs) for providing ubiquitous connectivity and control-ling …

Dietary adjustment through food group substitutions is an adaptive strategy for obesity
management in human populations and action on climate change. However, specific dietary …

Materials and Methods: This study was performed in 468 subjects (194 CRC patients and
274 non-CRC cases). We used the CRC dataset from the Imam Hospital, Sari, Iran. The Chi …

Student dropout issue is a major concern among the academics and management of the
university. The higher rate of student dropout impacted the university reputation such as …

Obesity has become one of the world's largest health issues, rich and poor countries, without
exception, have each year larger populations with this condition. Obesity and overweight are …