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Articoli di riviste sul tema "Personalized food"

Autore: Grafiati

Pubblicato: 24 agosto 2024

Ultima modifica: 19 luglio 2025

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1

Park, Seon Kyeong, and Jae-Ho Park. "Personalized food based on genomics." Food Science and Industry 56, no. 4 (2023): 290–300. http://dx.doi.org/10.23093/fsi.2023.56.4.290.

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Ujalambkar, Dr Deepali. "FoodX: An AI-Powered System for Packaged Food Ingredient Analysis and Personalized Health Recommendations." International Journal for Research in Applied Science and Engineering Technology 13, no. 5 (2025): 3262–70. https://doi.org/10.22214/ijraset.2025.70940.

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Abstract: This research presents a technology-driven solution aimed at simplifying the understanding of nutritional information in packaged food products. With the increasing consumption of processed food and rising health concerns, there is a growing need for tools that enable informed dietary decisions. The proposed system integrates optical character recognition (OCR), machine learning (ML), and natural language processing (NLP) to extract, analyze, and personalize nutritional data from product labels. By incorporating user-specific health profiles and real-time image processing, the system

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Zhao, Haiming, Jufeng Wang, Xiaoyu Ren, Jingyuan Li, Yong-Liang Yang, and Xiaogang Jin. "Personalized food printing for portrait images." Computers & Graphics 70 (February 2018): 188–97. http://dx.doi.org/10.1016/j.cag.2017.07.012.

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Horiguchi, Shota, Sosuke Amano, Makoto Ogawa, and Kiyoharu Aizawa. "Personalized Classifier for Food Image Recognition." IEEE Transactions on Multimedia 20, no. 10 (2018): 2836–48. http://dx.doi.org/10.1109/tmm.2018.2814339.

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Thongsri, Nattaporn, Pattaraporn Warintarawej, Santi Chotkaew, and Wanida Saetang. "Implementation of a personalized food recommendation system based on collaborative filtering and knapsack method." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 1 (2022): 630. http://dx.doi.org/10.11591/ijece.v12i1.pp630-638.

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Food recommendation system is one of the most interesting recommendation problems since it provides data for decision-making to users on selection of foods that meets individual preference of each user. Personalized recommender system has been used to recommend foods or menus to respond to requirements and restrictions of each user in a better way. This research study aimed to develop a personalized healthy food recommendation system based on collaborative filtering and knapsack method. Assessment results found that users were satisfied with the personalized healthy food recommendation system

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Nattaporn, Thongsri, Warintarawej Pattaraporn, Chotkaew Santi, and Saetang Wanida. "Implementation of a personalized food recommendation system based on collaborative filtering and knapsack method." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 1 (2022): 630–38. https://doi.org/10.11591/ijece.v12i1.pp630-638.

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Food recommendation system is one of the most interesting recommendation problems since it provides data for decision-making to users on selection of foods that meets individual preference of each user. Personalized recommender system has been used to recommend foods or menus to respond to requirements and restrictions of each user in a better way. This research study aimed to develop a personalized healthy food recommendation system based on collaborative filtering and knapsack method. Assessment results found that users were satisfied with the personalized healthy food recommendation system

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BETHKE, Malte, Lavinia MURESAN, and Monica TRIF. "OFTIFEL PERSONALIZED NUTRITIONAL CALCULATOR." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Food Science and Technology 73, no. 2 (2016): 151. http://dx.doi.org/10.15835/buasvmcn-fst:12270.

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A food calculator for elderly people was elaborated by Centiv GmbH, an active partner in the European FP7 OPTIFEL Project, based on the functional requirement specifications and the existing recommendations for daily allowances across Europe, data which were synthetized and used to give aims in amounts per portion. The OPTIFEL Personalised Nutritional Calculator is the only available online tool which allows to determine on a personalised level the required nutrients for elderly people (65+). It has been developed mainly to support nursing homes providing best possible (personalised) nutrient

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8

Karabay, Aknur, Arman Bolatov, Huseyin Atakan Varol, and Mei-Yen Chan. "A Central Asian Food Dataset for Personalized Dietary Interventions." Nutrients 15, no. 7 (2023): 1728. http://dx.doi.org/10.3390/nu15071728.

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Nowadays, it is common for people to take photographs of every beverage, snack, or meal they eat and then post these photographs on social media platforms. Leveraging these social trends, real-time food recognition and reliable classification of these captured food images can potentially help replace some of the tedious recording and coding of food diaries to enable personalized dietary interventions. Although Central Asian cuisine is culturally and historically distinct, there has been little published data on the food and dietary habits of people in this region. To fill this gap, we aim to c

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9

Zeisel, Steven H. "Precision (Personalized) Nutrition: Understanding Metabolic Heterogeneity." Annual Review of Food Science and Technology 11, no. 1 (2020): 71–92. http://dx.doi.org/10.1146/annurev-food-032519-051736.

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People differ in their requirements for and responses to nutrients and bioactive molecules in the diet. Many inputs contribute to metabolic heterogeneity (including variations in genetics, epigenetics, microbiome, lifestyle, diet intake, and environmental exposure). Precision nutrition is not about developing unique prescriptions for individual people but rather about stratifying people into different subgroups of the population on the basis of biomarkers of the above-listed sources of metabolic variation and then using this stratification to better estimate the different subgroups’ dietary re

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M.Yasaswini. "Longitudinal Dietary Optimization via Multi-Horizon Time Series Forecasting of BMI with Transformer Networks and Personalized Recommendation using Collaborative Filtering with Implicit Feedback." Journal of Information Systems Engineering and Management 10, no. 36s (2025): 01–12. https://doi.org/10.52783/jisem.v10i36s.6303.

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Long-term management of Body Mass Index (BMI) shows to be challenging for most people, mainly due to limitations in dietary compliance monitoring and the lack of personalized predictive guidance. Standard methods leave much to be desired when it comes to offering personalized, adaptable strategies aligned with our unique metabolic processes and changing preferences. To address this gap, this paper develops a new computational framework for longitudinal dietary optimization. We leverage early detection for BMI management as our system is powered by state-of-the-art machine learning algorithms t

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M, Gallas, and de Margerie V0. "Vertical Hot Melt Extrusion: A Cutting Edge Technology for Personalized and Sustainable Food Systems." Physical Science & Biophysics Journal 8, no. 2 (2024): 1–9. http://dx.doi.org/10.23880/psbj-16000276.

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New trends in the food industry are radically transforming how we produce, process, and consume food, creating new pathways for personalization, sustainability, and operational efficiency. Vertical Hot Melt Extrusion (HME) is a major innovation that offers unprecedented opportunities to create highly personalized food products tailored to specific dietary needs or remote locations, including nutrient-dense options designed for individual health requirements. All of this thanks to precise control over food texture, structure, and nutrient release while improving the solubility and stability of

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Nikitina, Marina, and Irina Chernukha. "Personalized nutrition and “digital twins” of food." Potravinarstvo Slovak Journal of Food Sciences 14 (May 28, 2020): 264–70. http://dx.doi.org/10.5219/1312.

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Mathematization of research is one of the most effective methods of virtual substantiation of foodstuff recipe and technology. This approach allows creating a product that meets consumer's individual needs, i.e. personalized foodstuff (ethnicity, cultural preferences, regional and environmental characteristics, lifestyle), and at the same time reducing the time and cost of decision-making. The article discusses the hypothesis that the “digital twin” of a food product is a virtual model of the product, namely its mathematical model (simulation model). A simulation model is a logical and mathema

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D’costa, Denzil Celestine. "A Study On 3d Printed Food and Its Potential for Personalized Nutrition." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem41940.

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The emergence of 3D food printing presents a transformative opportunity for personalized nutrition, allowing precise customization of meals based on individual dietary needs. This study explores the feasibility, benefits, and challenges of 3D printed food in creating personalized nutrition solutions. An experimental approach was employed, where nutrient-rich ingredients were formulated and printed using a 3D food printer. Nutritional and structural analyses confirmed that printed foods maintained their integrity while meeting targeted macronutrient and micronutrient compositions. Survey respon

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Jeon, Yoomin, Jung-Hyun Won, David Seung U. Lee, et al. "Development of a Questionnaire for the Personalized Health Functional Food." Korean Journal of Health Promotion 22, no. 1 (2022): 26–39. http://dx.doi.org/10.15384/kjhp.2022.22.1.26.

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Background: This study describes the development of a multi-dimensional questionnaire for the personalized recommendation of health functional foods.Methods: The questionnaire was designed to include two parts: common and detailed. Each question was formulated based on clinical evidence and physician-administered diagnostic tools provided by reputable sources such as government agencies and medical institutions. The common questions were intended to assess overall health status. The detailed questions were organized into 28 categories based on the classification of health functional foods’ hea

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Roosen, Jutta, Maike Bruhn, Rebecca-Ariane Mecking, and Larissa S. Drescher. "Consumer Demand for Personalized Nutrition and Functional Food." International Journal for Vitamin and Nutrition Research 78, no. 6 (2008): 269–74. http://dx.doi.org/10.1024/0300-9831.78.6.269.

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New developments in nutrigenetic research and the European regulation 1924/2006 on health claims have spurred interest in developing and marketing functional food designed for personalized nutrition. Personalized nutrition uses genetic information regarding a person’s health risk profile. Specifically adapted nutrition recommendations are claimed to help reducing disease risk. An internet survey was conducted in December 2007 using a sample of 452 randomly selected adults in Germany. The survey instrument assesses if consumers would be willing to participate in genetic risk profiling, if they

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Martirosyan, Danik, and Sarah Stratton. "Quantum and tempus theories of function food science in practice." Functional Food Science 3, no. 5 (2023): 55. http://dx.doi.org/10.31989/ffs.v3i5.1122.

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Functional food science has witnessed remarkable advancements in recent years, driven by our evolving understanding of quantum mechanics and the concept of time. The interplay between these two theories, namely the Quantum theory and the Tempus theory, has opened new avenues for research and innovation in functional food. Functional food science integrates these theories to better understand the complex relationship between food, chronic disease, and health. Quantum theory explores the molecular-level interplay between energy, matter, and bioactive compounds in functional foods, optimizing the

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TRIF, Monica, Lavinia MURESAN, and Malte BETHKE. "Personalised nutritional powder for elderly developed in OPTIFEL European Project." Bulletin of University of Agricultural Sciences and Veterinary Medicine Cluj-Napoca. Food Science and Technology 73, no. 2 (2016): 149. http://dx.doi.org/10.15835/buasvmcn-fst:12271.

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A personalized nutritional powder for elderly containing minerals and vitamins was developed by CENTIV GmbH for further applications in the FP7 European OFTIFEL project by designing and processing of novel food products such as nutrient dense smoothie products. The amount of the powder used for each person, in each product, is calculated using a food calculator, which was developed within the same FP7 European OFTIFEL project, named OPTIFEL Personalised Nutritional Calculator.The personalized nutritional powder consisting of several minerals and vitamins, has been agglomerated in a Fluid Bed D

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Manjula M, Jeevitha R S, Mithra Impens, Sirijalakshmi R, and Subhlashmy V. "Advanced Deep Learning Model for Food Recognition and Personalised Diet Planning." International Research Journal on Advanced Engineering and Management (IRJAEM) 3, no. 04 (2025): 1516–23. https://doi.org/10.47392/irjaem.2025.0247.

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Technology is becoming an important partner when the awareness grows about how our diet & lifestyle affect health. It helps people make better food choices—choices that are more informed. One of the most exciting advancements is using AI to identify the foods we eat and create personalized nutrition plans. Models like VGG16 have been used for food recognition, but they often fall short in accuracy. They do not have the data for tailored dietary suggestions. This shortcoming stops them from offering the best health solutions to users.To overcome these issues, we recommend the Inception V3 d

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Manivelkumar, Koushikha Namakkal, and Chinnappan A. Kalpana. "A Systematic Review on 3D Food Printing: Progressing from Concept to Reality." Amerta Nutrition 9, no. 1 (2025): 176–85. https://doi.org/10.20473/amnt.v9i1.2025.176-185.

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Background: Using 3D printing technology, novel items can be created from various materials, including edible ones, addressing the growing importance of sustainable food chains and personalized nutrition. As the latest advancement in additive manufacturing, 3D printing meets diverse customer demands by producing customized food items tailored to individual nutritional needs. Objectives: This literature evaluation focuses on the applications, technical advancements, and future possibilities of 3D food printing. By assessing recent developments, the study explores its adaptability and transforma

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Yao, Qisi, Haley Parker, Maya Vadiveloo, and Anne Thorndike. "Participant Characteristics Contributed to Variable Responsiveness to Personalized Healthy Food Incentives—A Secondary Analysis of a Randomized Crossover Trial." Current Developments in Nutrition 5, Supplement_2 (2021): 997. http://dx.doi.org/10.1093/cdn/nzab051_041.

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Abstract Objectives The recently completed Smart Cart Study, designed to promote healthier food purchases, found that personalized healthy food incentives modestly improved mean grocery purchase quality, with considerable variation in participant responsiveness. The present study explored participant characteristics associated with variable responsiveness to this healthy food incentives intervention. Methods A secondary analysis examined the Smart Cart Study, where participants received personalized weekly coupons during in the intervention and occasional generic coupons during the control per

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Mori, Francesca, Simona Barni, Giulia Liccioli, and Elio Novembre. "Oral Immunotherapy (OIT): A Personalized Medicine." Medicina 55, no. 10 (2019): 684. http://dx.doi.org/10.3390/medicina55100684.

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Oral Immunotherapy (OIT), a promising allergen-specific approach in the management of Food Allergies (FA), is based on the administration of increasing doses of the culprit food until reaching a maintenance dose. Each step should be adapted to the patient, and OIT should be considered an individualized treatment. Recent studies focused on the standardization and identification of novel biomarkers in order to correlate endotypes with phenotypes in the field of FA.

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Livingstone, Katherine, Carlos Celis-Morales, Santiago Navas-Carretero, et al. "Personalized Nutrition Advice Reduces Intake of Discretionary Foods and Beverages: Findings From the Food4Me Randomized Controlled Trial." Current Developments in Nutrition 5, Supplement_2 (2021): 152. http://dx.doi.org/10.1093/cdn/nzab035_060.

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Abstract Objectives This study aimed to examine changes in intake of discretionary foods and beverages following a personalized nutrition intervention using two national classifications for discretionary foods. Methods Participants were recruited into a 6-month RCT across seven European countries (Food4Me) and were randomized to receive generalized dietary advice (Control) or one of three levels of personalized nutrition advice (based on dietary, phenotypic and genotypic information). Dietary intake from a FFQ was used to determine change between baseline and month 6 in (i) % energy, % contrib

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Deschildre, A., S. Lejeune, M. Cap, et al. "Food allergy phenotypes: The key to personalized therapy." Clinical & Experimental Allergy 47, no. 9 (2017): 1125–37. http://dx.doi.org/10.1111/cea.12984.

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Kondo, Naomi, Manami Kuwabara, Hitomi Kodama, Masumi Kumada, and Nobuhiro Hori. "Medical treatment of food allergies should be personalized." Personalized Medicine Universe 4 (July 2015): 73–75. http://dx.doi.org/10.1016/j.pmu.2015.03.005.

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Frossard, Mikaël, Natalia Gasilova, Lionel Arlettaz, Eric Dayer, and Hubert H. Girault. "Personalized and rapid test for food-related allergy." Journal of Allergy and Clinical Immunology 141, no. 6 (2018): 2297–300. http://dx.doi.org/10.1016/j.jaci.2017.11.065.

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Ray, Subhasree. "Personalized Modification of Breast Milk to Help Enhancing Nutrition Profile of Neonates: A short Communication." Current Research in Nutrition and Food Science Journal 2, no. 1 (2014): 47–50. http://dx.doi.org/10.12944/crnfsj.2.1.07.

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Personalized Nutrition means in practice, adapting food to individual needs, depending on the host’s genome, this calls for an emerging field of nutrigenomic approach in order to build the tools for individualized diet, health maintenance and disease prevention. Based on this principle, breast milk is now being analyzed, modified and administered in smaller infants to provide them personalized diet, ensuring the premature infants are receiving correct amounts of nutrients they need to thrive. In the past, all milk was fortified to the same and it was ‘one-size-fits-all’. Now, nutrigenomics is

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YU, Qing, Masashi ANZAWA, Sosuke AMANO, and Kiyoharu AIZAWA. "Personalized Food Image Classifier Considering Time-Dependent and Item-Dependent Food Distribution." IEICE Transactions on Information and Systems E102.D, no. 11 (2019): 2120–26. http://dx.doi.org/10.1587/transinf.2019pcp0005.

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Yun, Hyun-Jung, Na-Ra Han, Hyun-Woo An, Won-Kyo Jung, Hyun-Woo Kim, and Sang-Gil Lee. "Development of an Abalone 3D Food Printing Ink for the Personalized Senior-Friendly Foods." Foods 11, no. 20 (2022): 3262. http://dx.doi.org/10.3390/foods11203262.

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Notably for seniors, 3D food printing is an appropriate processing method for creating customized meals that meet their unique nutritional requirements and textural preferences. This study attempted to develop an ink for food 3D printers containing abalone powder and several nutrition properties that meet the criteria for senior-friendly foods. The texture of the products was adjusted using gelatin. The ink consisted of abalone powder (10%), soybean protein (4.5%), polydextrose (2.5%), vitamin C (0.0098%), and gellan gum (1%). To examine the physicochemical properties of the ink, texture, wate

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Xie, Yisha, Qingqing Liu, Wenwen Zhang, et al. "Advances in the Potential Application of 3D Food Printing to Enhance Elderly Nutritional Dietary Intake." Foods 12, no. 9 (2023): 1842. http://dx.doi.org/10.3390/foods12091842.

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The contradiction between the growing demand from consumers for “nutrition & personalized” food and traditional industrialized food production has consistently been a problem in the elderly diet that researchers face and discuss. Three-dimensional (3D) food printing could potentially offer a solution to this problem. This article reviews the recent research on 3D food printing, mainly including the use of different sources of protein to improve the performance of food ink printing, high internal phase emulsion or oleogels as a fat replacement and nutrition delivery system, and functional a

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Aswan, Girishkumar, Asif S. Muhammed, Madhav Rohan, S. Suneer, and George Jomy. "Food Image Recognition and Nutrients Tracker." Journal of Advance Research in Mobile Computing 6, no. 3 (2024): 23–36. https://doi.org/10.5281/zenodo.13235205.

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<em>The project introduces a web-based food image recognition and nutrient tracker, merging deep learning with web technologies to redefine dietary monitoring. Crafted with HTML, CSS, and Javascript, the user interface offers a seamless experience, enabling users to effortlessly capture food images, view identified items with corresponding nutrient information, and track intake within a visually appealing dashboard, complete with personalized insights and recommendations. Python orchestrates the back-end, utilizing the YOLOv8 deep learning model for real-time object detection, accurately ident

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Ribeiro, David, Telmo Barbosa, Jorge Ribeiro, et al. "SousChef System for Personalized Meal Recommendations: A Validation Study." Applied Sciences 12, no. 2 (2022): 702. http://dx.doi.org/10.3390/app12020702.

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Nutrition is an essential part of our life. A healthy diet can help to prevent several chronic diseases like diabetes, obesity, cancer, and cardiovascular diseases, being influenced by social, cultural, and economic factors. Meal recommender systems are a trend to assist people in finding new recipes to cook and adopt healthier eating habits. However, food choice is complex and driven by multiple factors which need to be reflected in the personalization process of these systems to ensure their adoption. We present SousChef, a meal recommender system that can help to plan multiple meals conside

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Héritier, Harris, Chloé Allémann, Oleksandr Balakiriev, et al. "Food & You: A digital cohort on personalized nutrition." PLOS Digital Health 2, no. 11 (2023): e0000389. http://dx.doi.org/10.1371/journal.pdig.0000389.

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Nutrition is a key contributor to health. Recently, several studies have identified associations between factors such as microbiota composition and health-related responses to dietary intake, raising the potential of personalized nutritional recommendations. To further our understanding of personalized nutrition, detailed individual data must be collected from participants in their day-to-day lives. However, this is challenging in conventional studies that require clinical measurements and site visits. So-called digital or remote cohorts allow in situ data collection on a daily basis through m

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Mahesh, Sahana. "OCR and NLP based Personalized Allergen Notifying System." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 02 (2025): 1–9. https://doi.org/10.55041/ijsrem41634.

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This project focuses on developing a personalized allergen notification system to help individuals identify potential allergens in food products based on their dietary preferences and known allergens. A key feature of this system is Optical Character Recognition (OCR), which enables users to scan ingredient lists directly from product packaging. The OCR technology extracts text from images of ingredients, which is then processed using natural language processing (NLP) and machine learning algorithms to compare the extracted text against the user's allergen profile. The system provides real-tim

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Ali, Adli, Nur Hana Hamzaid, and Noor Akmal Shareela Ismail. "The Interplay of Nutriepigenomics, Personalized Nutrition and Clinical Practice in Managing Food Allergy." Life 11, no. 11 (2021): 1275. http://dx.doi.org/10.3390/life11111275.

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Food allergy in children has been a common issue due to the challenges of prescribing personalized nutrition with a lack of nutriepigenomics data. This has indeed further influenced clinical practice for appropriate management. While allergen avoidance is still the main principle in food allergy management, we require more information to advance the science behind nutrition, genes, and the immune system. Many researchers have highlighted the importance of personalized nutrition but there is a lack of data on how the decision is made. Thus, this review highlights the relationship among these ke

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Huang, Shuchang, Cungang Wang, and Wei Bian. "A Hybrid Food Recommendation System Based on MOEA/D Focusing on the Problem of Food Nutritional Balance and Symmetry." Symmetry 16, no. 12 (2024): 1698. https://doi.org/10.3390/sym16121698.

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With the improvement of people’s living standards, the issue of dietary health has received extensive attention. In order to simultaneously meet people’s demands for dietary preferences and nutritional balance, we have conducted research on the issue of personalized food recommendations. For this purpose, we have proposed a hybrid food recommendation model, which can provide users with scientific, reasonable, and personalized dietary advice. Firstly, the collaborative filtering (CF) algorithm is adopted to recommend foods to users; then, the improved Multi-Objective Evolutionary Algorithm Base

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Barrow, Michelle, Linda Bell, and Celia Bell. "Transforming personalized nutrition practice." Nutrition Reviews 78, no. 12 (2020): 1046–51. http://dx.doi.org/10.1093/nutrit/nuaa012.

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Abstract The strengths and limitations of current approaches to clinical nutrition practice and their underpinning research are explored in this article. It describes how a personalized nutrition practice approach supported by evidence-based pathophysiological reasoning could direct additional research, which could then transform practice and support food industry developments. Current use of the term “personalized nutrition” is reviewed and a definition is provided. Also explored are current approaches to personalized nutrition practice and evidence-based practice in clinical nutrition. Patie

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Matthew, N. O. Sadiku, J. Ashaolu Tolulope, and M. Musa Sarhan. "Smart Food An Introduction." International Journal of Trend in Scientific Research and Development 4, no. 2 (2020): 121–24. https://doi.org/10.5281/zenodo.3842995.

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Smart technology is an important part of the solution to food challenges. Smart technologies are already being used by urban food projects but the two concepts are not well connected. Smart Food has been introduced as approach to provide a personalized, mobile, on site counseling service for food allergic people. Smart food focuses especially on foods that can be eaten as staples. This paper provides a brief introduction to smart food. Matthew N. O. Sadiku | Tolulope J. Ashaolu | Sarhan M. Musa "Smart Food: An Introduction" Published in International Journal of Trend in Scientific Re

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Toribio-Mateas, Miguel A., and Tim D. Spector. "Could food act as personalized medicine for chronic disease?" Personalized Medicine 14, no. 3 (2017): 193–96. http://dx.doi.org/10.2217/pme-2016-0017.

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Oh, Yoori, Jieun Choi, and Yoonhee Kim. "A Personalized Dietary Coaching Method Using Food Clustering Analysis." KIPS Transactions on Software and Data Engineering 5, no. 6 (2016): 289–94. http://dx.doi.org/10.3745/ktsde.2016.5.6.289.

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Jeon, So-Hye, and Nam-Hyun Kim. "Diabetes Risk Analysis Model with Personalized Food Intake Preference." Journal of the Korea Academia-Industrial cooperation Society 14, no. 11 (2013): 5771–77. http://dx.doi.org/10.5762/kais.2013.14.11.5771.

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Coskun, Ahmet F., Justin Wong, Delaram Khodadadi, Richie Nagi, Andrew Tey, and Aydogan Ozcan. "A personalized food allergen testing platform on a cellphone." Lab Chip 13, no. 4 (2013): 636–40. http://dx.doi.org/10.1039/c2lc41152k.

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Jeong, Yong-Yun, Min-Gyu Park, Gun-Woo Kim, Seok-hwan Kim, and Kyoung-Shin Park. "A Comparative Evaluation Study on Personalized Food Recommendation Algorithms." Journal of the Korea Institute of Information and Communication Engineering 27, no. 3 (2023): 318–27. http://dx.doi.org/10.6109/jkiice.2023.27.3.318.

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Kim, Youjin, Seunghee Kang, Soyoung Maeng, Eunbi Huh, and Oran Kwon. "Industry trends in Personalized food based on nutritional stuatus." Food Science and Industry 56, no. 4 (2023): 301–20. http://dx.doi.org/10.23093/fsi.2023.56.4.301.

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Ruskina, Alena, Alena Astaeva, Irina Potoroko, and Anna Shtrakhova. "Food systems for personalized replacement technologies for health preservation." Bulletin of the South Ural State University Series Food and Biotechnology 12, no. 1 (2024): 68–75. https://doi.org/10.14529/food240108.

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Abstract (sommario):

The scientific community has established a correlation between the quality of nutri-tion and depression that occurs against the background of the development of NCDs (in particular, type 2 diabetes). For the majority of the population, the identified problem is due to the state of the environment, existing non-communicable diseases (NCDs), provoking changes in the subject’s eating behavior patterns, and, as a consequence, disruption of the body’s metabolic processes. In the psychological aspect, the PP style reflects the needs and emotional state of a person. Therefore, one of the most importa

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Wang, Lifeng, Qing Meng, and Chun-Hsien Su. "From Food Supplements to Functional Foods: Emerging Perspectives on Post-Exercise Recovery Nutrition." Nutrients 16, no. 23 (2024): 4081. http://dx.doi.org/10.3390/nu16234081.

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Abstract (sommario):

Effective post-exercise recovery is vital for optimizing athletic performance, focusing on muscle repair, glycogen replenishment, rehydration, and inflammation management. This review explores the evolving trend from traditional supplements, such as protein, carbohydrates, creatine, and branched-chain amino acids (BCAAs), toward functional foods rich in bioactive compounds. Evidence highlights the benefits of functional foods like tart cherry juice (anthocyanins), turmeric-seasoned foods, and sources of omega-3 fatty acids, including fish, flaxseeds, chia seeds, and walnuts, for mitigating oxi

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Parate, Asst Prof Roshani. "Cross Platform Application for Food Delivery Services." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem28259.

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Abstract (sommario):

In the ever-developing field of food delivery services, the " Cross-Platform Application for Food Delivery Services " prototype project brings great solutions to close this gap. The project aims to create a comprehensive and user-friendly platform that perfectly meets the needs and demands of today's customers. With the proliferation of smartphones and the transition to online services and applications, food delivery has become an important part of almost everyone's life, that is, their daily life. However, existing applications often fall short of providing a real and personalized experience,

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Rudkowska, Iwona. "Genomics and Personalized Nutrition." Nutrients 13, no. 4 (2021): 1128. http://dx.doi.org/10.3390/nu13041128.

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Tejada-Ortigoza, Viridiana, and Enrique Cuan-Urquizo. "Towards the Development of 3D-Printed Food: A Rheological and Mechanical Approach." Foods 11, no. 9 (2022): 1191. http://dx.doi.org/10.3390/foods11091191.

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Abstract (sommario):

Additive manufacturing, or 3D printing, has raised interest in many areas, such as the food industry. In food, 3D printing can be used to personalize nutrition and customize the sensorial characteristics of the final product. The rheological properties of the material are the main parameters that impact the 3D-printing process and are crucial to assuring the printability of formulations, although a clear relationship between these properties and printability has not been studied in depth. In addition, an understanding of the mechanical properties of 3D-printed food is crucial for consumer sati

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Spector, Tim, Francesco Asnicar, Sarah Berry, et al. "Microbiome Signatures of Nutrients, Foods and Dietary Patterns: Potential for Personalized Nutrition from The PREDICT 1 Study." Current Developments in Nutrition 4, Supplement_2 (2020): 1587. http://dx.doi.org/10.1093/cdn/nzaa062_044.

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Abstract (sommario):

Abstract Objectives The human gut microbiome has been linked to risk and severity of a multitude of chronic diseases, but large-scale, high-resolution studies linking it to host diet are lacking. The PREDICT 1 study (NCT03479866) enrolled 1,102 healthy US and UK adults to examine the genetic, metabolic, microbial, and meal composition/context contributions to metabolic responses to food. Here, we identify microbial features (species, genes, pathways) linked with diet and assess their potential to predict personalized food responses. Methods Dietary intake was assessed using validated EPIC (UK)

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Manish Kumar Sharma, Anmol Gupta, and Yatharth Chauhan. "Harnessing Artificial Intelligence for Predictive Analytics in Culinary Trends, Personalized Nutrition, and Automated Cooking Systems: A Technological Shift in Future Food Innovation." International Journal for Multidimensional Research Perspectives 3, no. 6 (2025): 13–25. https://doi.org/10.61877/ijmrp.v3i6.286.

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Abstract (sommario):

This study explores the transformative impact of Artificial Intelligence (AI) on the food industry, particularly in predictive analytics for culinary trends, personalized nutrition, and automated cooking systems. AI's ability to process vast datasets and generate actionable insights is revolutionizing how food businesses predict and adapt to evolving consumer preferences and dietary trends. Predictive analytics, powered by machine learning algorithms, enables businesses to anticipate market shifts, ensuring timely product development and minimizing food waste. In personalized nutrition, AI is

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