A fuzzy based dietary clinical decision support system for patients with multiple chronic conditions (MCCs).

Due to the multifaceted nature of Multiple Chronic Conditions (MCCs), setting a diet for these patients is complicated and time-consuming. In this study, a clinical decision support system based on fuzzy logic was modeled and evaluated to aid dietitians in adjusting the diet for patients with MCCs. Mamdani fuzzy logic with 1144 rules was applied to design the model for MCCs patients over 18 years who suffer from one or more chronic diseases, including obesity, diabetes, hypertension, hyperlipidemia, and kidney disease.

Determining the effective factors in predicting diet adherence using an intelligent model.

Adhering to a healthy diet plays an essential role in preventing many nutrition-related diseases, such as obesity, diabetes, high blood pressure, and other cardiovascular diseases. This study aimed to predict adherence to the prescribed diets using a hybrid model of artificial neural networks (ANNs) and the genetic algorithm (GA). In this study, 26 factors affecting diet adherence were modeled using ANN and GA(ANGA).

Machine Learning Models to Predict In-Hospital Mortality among Inpatients with COVID-19: Underestimation and Overestimation Bias Analysis in Subgroup Populations.

Prediction of the death among COVID-19 patients can help healthcare providers manage the patients better. We aimed to develop machine learning models to predict in-hospital death among these patients. We developed different models using different feature sets and datasets developed using the data balancing method.

Physical activity and sedentary behaviors (screen time and homework) among overweight or obese adolescents: a cross-sectional observational study in Yazd, Iran.

Background: The growing number of adolescents who are overweight or obese (OW / OB) is a public concern. The present study was aimed to evaluate physical activity (PA) and sedentary behaviors (SB) (screen time (ST) and homework time (HT)) among Yazd OW/OB adolescents.

Methods: This cross-sectional study was performed among 510 students aged 12-16 in Yazd, Iran.

Effect of implementing a mobile game on improving dietary information in diabetic patients.

Nowadays, digital games are not just entertainment, but beside routine treatments, they are used in patient care, especially in patients with diabetes. Application of digital games in patient's education can improve self-management of diabetes. The aim of the present study was to evaluate the effect of a mobile game (Amoo) implementation on enhancing dietary information in patients with type 2 diabetes.