ArticleScientific reports2022
Determining the effective factors in predicting diet adherence using an intelligent model.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Machine Learning for the Analysis of Healthy Lifestyle Data: Scoping Review and Guidelines.JMIR human factors · 2026Guideline
- The Challenges of Performing Controlled Trials of Diet Therapies in Gastroenterology.JGH open : an open access journal of gastroenterology and hepatology · 2026Review
- Mediterranean Lifestyle Adherence Reflects Coherent Behavioural Patterns Based on the MEDLIFE Index.Nutrients · 2026Observational
- Ammonium Hydroxide Enhancement of Dietary Protein in High-Fat Diets Modulates Liver Metabolism Signaling in a Sex- and Age-Dependent Manner in C3H/HeJ Mice.International journal of molecular sciences · 2025Article
- Predicting diet quality and food consumption at eating occasions using contextual factors: an application of machine learning models.The international journal of behavioral nutrition and physical activity · 2025Article
- Determining the Importance of Lifestyle Risk Factors in Predicting Binge Eating Disorder After Bariatric Surgery Using Machine Learning Models and Lifestyle Scores.Obesity surgery · 2025Article
- Patient experiences with and adherence to Crohn's disease exclusion diet in Dutch Crohn's disease patients: a cohort study.Therapeutic advances in gastroenterology · 2025Article
- Article
- Adopting machine learning to predict breast cancer patients adherence with lifestyle recommendations and quality of life outcomes.Frontiers in digital health · 2025Article
- A Higher Adherence to the ALINFA Nutritional Intervention Is Effective for Improving Dietary Patterns in Children.Children (Basel, Switzerland) · 2024Article
- Sequential model for predicting patient adherence in subcutaneous immunotherapy for allergic rhinitis.Frontiers in pharmacology · 2024Article
- Genetic variant panel allows predicting both obesity risk, and efficacy of procedures and diet in weight loss.Frontiers in nutrition · 2023Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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). A dataset of 1528 patients, including 1116 females and 412 males, referred to a private clinic was applied. SPSS Ver.25 and MATLAB toolbox 2017 were employed to make the model and analyze the data. The results showed that the accuracy of the proposed ANN and ANGA models for predicting diet adherence was 93.22% and 93.51%, respectively. Also, the Pearson coefficient showed a significant relationship among the factors. The developed model showed the proper performance for predicting adherence to the diet. Moreover, the most effective factors were selected using GA. Some important factors that affect diet adherence include the duration of the marriage, the reason for referring to the clinic, weight, body mass index (BMI), weight satisfaction, lunch and dinner times, and sleep time. Therefore, applying the proposed model can help dietitians identify people who need more support to adhere to the diet.
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