• Journal of Nutrition and Health
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• v.55 no.1
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• pp.1-9
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• 2022

In the past few decades, great progress has been made on understanding the interaction between nutrition and health status. But despite this wealth of knowledge, health problems related to nutrition continue to increase. This leads us to postulate that the continuing trend may result from a lack of consideration for intra-individual biological variation on dietary responses. Precision nutrition utilizes personal information such as age, gender, lifestyle, diet intake, environmental exposure, genetic variants, microbiome, and epigenetics to provide better dietary advices and interventions. Recent technological advances in the artificial intelligence, big data analytics, cloud computing, and machine learning, have made it possible to process data on a scale and in ways that were previously impossible. A big data platform is built by collecting numerous parameters such as meal features, medical metadata, lifestyle variation, genome diversity and microbiome composition. Sophisticated techniques based on machine learning algorithm can be used to integrate and interpret multiple factors and provide dietary guidance at a personalized or stratified level. The development of a suitable machine learning algorithm would make it possible to suggest a personalized diet or functional food based on analysis of intra-individual metabolic variation. This novel precision nutrition might become one of the most exciting and promising approaches of improving health conditions, especially in the context of non-communicable disease prevention.

• Journal of Food Hygiene and Safety
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• v.26 no.4
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• pp.302-307
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• 2011

One of the most important objectives of post-marketing monitoring of dietary supplements is the early detection of unknown and unexpected adverse events (AEs). Several causality algorithms, such as the Naranjo scale, the RUCAM scale, and the M & V scale are available for the estimation of the likelihood of causation between a product and an AE. Based on the existing algorithms, the Korea Food & Drug Administration has developed a new algorithm tool to reflect the characteristics of dietary supplements in the causality analysis. However, additional work will be required to confirm if the newly developed algorithm tool has reasonable sensitivity and not to generate an unacceptable number of false positives signals.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.73-78
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• 2023

Diabetes is chronic disease that is rapidly increasing in prevalence around the world, and mortality from complications continues to rise. This has made blood glucose management a critical challenge for modern society. The main methods used to manage blood glucose are diet, exercise, and medication. Among these, diet is one of the fundamental foundations of blood glucose management, avoiding foods that cause high blood glucose and minimizing blood glucose fluctuations, and is more accessible to people with diabetes as well as the general population. Currently, several platforms, both domestic and international, offer meal planning services, but this is mainly done by users or professional coaches. Accordingly, this paper implements an accurate Kcal calculation model based on DNN and presents a series of dietary algorithms for blood glucose management based on this.

• Korean Journal of Artificial Intelligence
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• v.11 no.3
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• pp.29-34
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• 2023

Recently, the rapid development of artificial intelligence technology, many studies are being conducted to predict the risk of heart disease in order to lower the mortality rate of cardiovascular diseases worldwide. This study presents exercise or dietary improvement contents in the form of a software app or web to patients with cardiovascular disease, and cardiovascular disease through digital devices such as mobile phones and PCs. LR, LDA, SVM, XGBoost for the purpose of developing "Life style Improvement Contents (Digital Therapy)" for cardiovascular disease care to help with management or treatment We compared and analyzed cardiovascular disease prediction models using machine learning algorithms. Research Results XGBoost. The algorithm model showed the best predictive model performance with overall accuracy of 80% before and after. Overall, accuracy was 80.0%, F1 Score was 0.77~0.79, and ROC-AUC was 80%~84%, resulting in predictive model performance. Therefore, it was found that the algorithm used in this study can be used as a reference model necessary to verify the validity and accuracy of cardiovascular disease prediction. A cardiovascular disease prediction analysis algorithm that can enter accurate biometric data collected in future clinical trials, add lifestyle management (exercise, eating habits, etc.) elements, and verify the effect and efficacy on cardiovascular-related bio-signals and disease risk. development, ultimately suggesting that it is possible to develop lifestyle improvement contents (Digital Therapy).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.2910-2925
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• 2017

Inadequate and inappropriate intake of food is known to cause various health issues and diseases. Due to lack of concise information about healthy diet, people have to rely on medicines instead of taking preventive measures in food intake. Due to diversity in food components and large number of dietary sources, it is challenging to perform real-time selection of diet patterns that must fulfill one's nutrition needs. Particularly, selection of proper diet is critical for patients suffering from various diseases. In this article, we highlight the issue of selection of proper diet that must fulfill patients' nutrition requirements. To address this issue, we present a cloud based food recommendation system, called Diet-Right, for dietary recommendations based on users' pathological reports. The model uses ant colony algorithm to generate optimal food list and recommends suitable foods according to the values of pathological reports. Diet-Right can play a vital role in controlling various diseases. The experimental results show that compared to single node execution, the convergence time of parallel execution on cloud is approximately 12 times lower. Moreover, adequate accuracy is attainable by increasing the number of ants.

• Korean Journal of Community Nutrition
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• v.10 no.5
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• pp.592-602
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• 2005

This study was conducted to compare nutrient intakes regarding stages of change in dietary fiber increasing behavior. Subjects were consisted of healthy 383 college students (2S0 females and 133 males) in Kyunggi-Do. Stages of change classified by an algorithm based on 6 items were designed each subjects into one of the 5 stages: precontemplation (PC), contemplation (CO), preparation (PR), action (AC), maintenance (MA). Nutrient intakes were assessed by 24-hr recall method. Regarding the S stages of changes, PR stage comprised the largest group $(39.4\%)$, followed by AC $(33.7\%)$, MA$(14.6\%)$, PC$(7.6\%)$, CO$(34.7\%)$. Female were more belong to either AC or MA. The higher stage of change in dietary fiber increasing behavior, the higher self-efficacy. In all male and female, there were no differences in energy, protein, monounsaturated fatty acids, polyunsaturated fatty acids and cholesterol intakes across the 5 stages. But, fiber, postassuim (K), vitamin A and vitamin C intakes of AC or MA were higer than those of PC, CO and PR $Energy\%$ from fat of $PR(25.4\~26.5\%)$ was higher than $20\%$, and those of AC and MA was lower than the other groups. Dietary P/S and ${\varepsilon}6/{\varepsilon}$ 3 ratios of AC and MA were similar to the recommended ratio. Female of PR had the most total saturated fat and palmitic acid and those of MA had the least. Male of PR had the least $\alpha-LNA\;({\varepsilon}3)$ and total ${\varepsilon}3$ fatty acids and those of MA had the most. In male and female in AC or MA, fiber and K intakes from breakfast, dinner and snack and vitamin C intakes from all meals were higher than those of the other stages. These results of our study confirm differences in stages of change in fiber intake in terms of nutritional status. To have lower $energy\%$ from fat, higher intakes of K, fiber and vitamins, desirable ratio of dietary fatty acids, it needs consistent nutritional education leading to the AC or MA of fiber increasing behavior.

• Nutrition Research and Practice
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• v.11 no.3
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• pp.247-256
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• 2017

BACKGROUND/OBJECTIVES: Easy access to intervention and support for certain behaviors is important for obesity prevention and management. The available technology such as smartphone applications can be used for intervention regarding healthy food choices for obesity prevention and management in elementary-school students. The transtheoretical model (TTM) is comprised of stages and processes of change and can be adopted to tailored education for behavioral change. This study aims to develop TTM-based nutrition contents for mobile applications intended to change eating behaviors related to weight gain in young children. SUBJECTS/METHODS: A synthesized algorithm for tailored nutrition messages was developed according to the intake status of six food groups (vegetables, fruits, sugar-sweetened beverages, fast food and instant food, snacks, and late-night snacks), decision to make dietary behavioral changes, and self-confidence in dietary behavioral changes. The messages in this study were developed from December 2014 to April 2015. After the validity evaluation of the contents through expert consultation, tailored nutrition information messages and educational contents were developed based on the TTM. RESULTS: Based on the TTM, stages of subjects are determined by their current intake status, decision to make dietary behavioral changes, and self-confidence in dietary behavioral changes. Three versions of tailored nutrition messages at each TTM stage were developed so as to not send the same messages for three weeks at most, and visual materials such as figures and tables were developed to provide additional nutritional information. Finally, 3,276 tailored nutrition messages and 60 nutrition contents for applications were developed. CONCLUSIONS: Smartphone applications may be an innovative medium to deliver interventions for eating behavior changes directly to individuals with favorable cost-effectiveness. In addition, using the TTM for tailored nutrition education for healthy eating is an effective approach.

• Archives of Obesity and Metabolism
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• v.1 no.2
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• pp.53-58
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• 2022

While the rising epidemic of obesity is primarily attributed to a sedentary lifestyle, poor dietary habits, and the aging of the population, secondary causes of obesity generally go undetected and untreated. These include endocrinological disorders, such as Cushing's syndrome, polycystic ovary syndrome, hypothalamic obesity, hypogonadism, and hypothyroidism, as well as genetic, syndromic, and drug-related obesity. We present an overview of the major disorders associated with obesity, highlighting the pathophysiologic mechanisms and discussing the diagnostic and treatment strategies that are most helpful to practicing physicians in recognizing and treating these generally under-detected and undertreated disorders.

• Journal of the Korean Society of Food Science and Nutrition
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• v.33 no.8
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• pp.1327-1336
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• 2004

This study was conducted to compare nutrient intakes regarding stages of change in dietary fat reduction behavior. Subjects were consisted of healthy 383 college students (250 females and 133 males) in Gyeonggi-Do. Stages of change classified by an algorithm based on 6 items were designed each subjects into one of the 5 stages: precontemplation (PC), contemplation (CO), preparation (PR), action (AC), maintenance (MA). Nutrient intakes were assessed by 24-hr recall method. Regarding the 5 stages of changes, PR stage comprised the largest group (31.1%), followed by AC (28.7%), PC (19.3%), CO (13.8%), MA (7.1%). Female were more belong to either AC or MA. Those in PC and PR had the most energy, fat, saturated fatty acid and cholesterol (except male) and those in AC and MA had the least. These dietary patterns were more distinctive in female than in male. The higher stage of change in dietary fat reduction behavior, the higher self-efficacy. Energy % from fat in PC, CO, PR was too higher than 20%, that of in AC and MA (except male in MA) was within 20%. The average P/S and $\omega$6/$\omega$3 ratio of diet fat for female were similar to the recommended ratio, but the average $\omega$6/$\omega$3 ratio for male was found to be 10.1～12.9, which was beyond the suggested range, 4～10. In male, energy, fat and protein intakes from dinner were significantly different among stages of change, but in female, besides dinner, those from breakfast, lunch and snack were significantly different among stages of change. These results of our study confirm differences in stages of change in fat intake in terms of nutritional status, especially in female, and indicate the need for taking these phases of changes into account in nutrition advice.

• Pediatric Gastroenterology, Hepatology & Nutrition
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• v.10 no.2
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• pp.117-128
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• 2007

Food protein-induced enterocolitis syndrome (FPIES) is a non-IgE mediated hypersensitivity disorder, which is associated with mainly gastrointestinal symptoms and has a delayed onset. The vomiting and/or diarrheal symptoms of FPIES typically begin in the first month of life in association with a failure to thrive, metabolic acidosis, and shock. Therefore, the differential diagnosis of FPIES and neonatal or infantile sepsis-like illnesses or gastroenteritis is difficult. The early recognition of indexes of suspicion for FPIES may help in the diagnosis and treatment of this disorder. The diagnosis of FPIES is generally made through clinical practice and food-specific IgE test findings are typically negative in this condition. Therefore, oral cow's milk challenge (OCC) remains the valid diagnostic standard for FPIES. An investigation of positive OCC outcomes helps to find out a diagnostic algorithm of criteria of a positive challenge in FPIES. Moreover, it has not been clearly determined in infantile FPIES when $1^{st}$ follow up-oral food challenge (FU-OFC) should be performed, with what kind of food protein (e.g., cow's milk, soy), and how much protein should be administered. Hence, to prevent the risk of inappropriate FU-OFC or accidental exposure and achieve appropriate dietary management, it is necessary to identify tolerance rates to major foods under the careful follow up of infantile FPIES patients. On the other hand, small intestinal enteropathy with villous atrophy is observed in FPIES and this enteropathy seems to be in part induced by both of epithelial apoptosis and intercellular junctional complex breakdown. The purpose of this report is to introduce an update on diagnostic and therapeutic approaches in FPIES and suggest the possible histopathological evidences in this disorder.