Annual Review of Nutrition, Год журнала: 2023, Номер 43(1)
Опубликована: Май 17, 2023
An interview with James M. Ntambi, professor of biochemistry and the Katherine Berns Van Donk Steenbock Professor in Nutrition, College Agricultural Life Sciences, at University Wisconsin–Madison, took place via Zoom April 2022. He was ...Read More
Язык: Английский
Nutrients, Год журнала: 2025, Номер 17(1), С. 190 - 190
Опубликована: Янв. 5, 2025
Background: Artificial Intelligence (AI) technologies are now essential as the agenda of nutrition research expands its scope to look at intricate connection between food and health in both an individual a community context. AI also helps tracing offering solutions dietary assessment, personalized clinical nutrition, well disease prediction management, such cardiovascular diseases, diabetes, cancer, obesity. This review aims investigate assess different applications roles understand potential future impact. Methods: We used PubMed, Scopus, Web Science, Google Scholar, EBSCO databases for our search. Results: Our findings indicate that is reshaping field ways were previously unimaginable. By enhancing how we diets, customize plans, manage complex conditions, has become tool. Technologies like machine learning models, wearable devices, chatbot revolutionizing accuracy tracking, making it easier than ever provide tailored individuals communities. These innovations proving invaluable combating diet-related illnesses encouraging healthier eating habits. One breakthrough been where significantly reduced errors common traditional methods. Tools use visual recognition, deep learning, mobile have made possible analyze nutrient content meals with incredible precision. Conclusions: Moving forward, collaboration tech developers, healthcare professionals, policymakers, researchers will be essential. focusing on high-quality data, addressing ethical challenges, keeping user needs forefront, can truly revolutionize science. The enormous. set make not only more effective but equitable accessible everyone.
Язык: Английский
Процитировано
2
Journal of Endocrinological Investigation, Год журнала: 2025, Номер unknown
Опубликована: Фев. 19, 2025
Язык: Английский
Процитировано
2
Journal of Personalized Medicine, Год журнала: 2024, Номер 14(3), С. 254 - 254
Опубликована: Фев. 27, 2024
Diet management has long been an important practice in healthcare, enabling individuals to get insight into their nutrient intake, prevent diseases, and stay healthy. Traditional methods based on self-reporting, food diaries, periodic assessments have used for a time control dietary habits. These shown limitations accuracy, compliance, real-time analysis. The rapid advancement of digital technologies revolutionized including the diet landscape, allowing innovative solutions patterns generate accurate personalized recommendations. This study examines potential effectiveness anti-aging healthcare. After underlining importance nutrition aging process, we explored applications mobile apps, web-based platforms, wearables devices, sensors, Internet Things, artificial intelligence, blockchain, other managing improving health outcomes. research further effects improved nutritional monitoring, recommendations, behavioral sustainable changes habits, leading expansion longevity span. challenges monitoring are discussed, some future directions provided. Although many tools control, effectiveness, impact outcomes not discussed much. review consolidates existing literature using emerging analyze practical implications, guiding researchers, healthcare professionals, policy makers toward healthy aging.
Язык: Английский
Процитировано
12
Опубликована: Фев. 26, 2024
This article examines the impact of Artificial Intelligence (AI) on comprehensive rehabilitation post-cancer patients, specifically in areas psychological support and cognitive rehabilitation. AI platforms demonstrate ability to provide personalized interventions real-time by utilizing advanced machine learning techniques such as Natural Language Processing (NLP), Random Forests, Long Short-Term Memory (LSTM) networks. The research explores use nutritional management for care, including genomic-based dietary plans nutrient-drug interactions. It emphasizes rapidly adapt experiences, showing its potential enhance treatment outcomes. highlights need interdisciplinary collaboration ensure ethical effective implementation emerging technologies. Additional is recommended verify effectiveness these models larger more diverse groups patients.
Язык: Английский
Процитировано
6
Applied Microbiology, Год журнала: 2024, Номер 4(4), С. 1677 - 1701
Опубликована: Дек. 16, 2024
Background: Autism spectrum disorder is a multifactorial phenomenon whose genetic, biological, environmental, and nutritional factors outline the heterogeneous phenotype of disease. A limitation in social connections with others, stereotyped reactions, specific interests preferences characterize behavioral manifestations person autism. Also, weaknesses are found emotional, cognitive, metacognitive development, significantly burdening individual’s quality life. Lately, it has gained widespread acceptance that gut microbiome neurotransmission constitute two decisive etiological autism both prenatal period postnatally. This study aims to investigate data on interaction between quantitative qualitative composition flora humans, as well their influences appearance progression symptoms disorder. At same time, captures role digital technology diagnosing intervening autism, which mainly related individual subjects under study. Methods: The current research employs an exploratory review provide concise overview complex neuronal functions associated neurotransmitter action homeostasis mechanisms allow brain human body survive perform optimally. Results: 111 sources highlighted connection dietary habits synthesizing releasing neurotransmitters influence emergence autism-related behaviors. Conclusions: literature review’s findings revealed importance performance behavioral, social, cognitive development among individuals Moreover, noteworthy combining healthy lifestyle targeted use tools can improve intensity symptoms.
Язык: Английский
Процитировано
4
Journal of Experimental Biology and Agricultural Sciences, Год журнала: 2025, Номер 12(6), С. 784 - 799
Опубликована: Янв. 15, 2025
The rapid advancement of emerging technologies is transforming the food industry, especially in enhancing nutritional qualities food. These innovations have significant potential for tackling global deficiencies and promoting public health. Key include precision fermentation, which enables production high-quality proteins micronutrients while minimizing environmental impact. Additionally, gene editing techniques such as CRISPR allow development crops with improved nutrient profiles enhanced resistance to pests diseases. Furthermore, advancements nanotechnology enhance fortification foods essential vitamins minerals, improving their bioavailability stability. Personalized nutrition, driven by big data artificial intelligence, customizes dietary recommendations based on individual genetic profiles, optimizing intake health outcomes. This review article overviews these cutting-edge applications creating a more nutritious sustainable system.
Язык: Английский
Процитировано
0
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Current Nutrition Reports, Год журнала: 2025, Номер 14(1)
Опубликована: Март 15, 2025
Язык: Английский
Процитировано
0
European Journal of Clinical Nutrition, Год журнала: 2023, Номер 78(1), С. 74 - 76
Опубликована: Окт. 13, 2023
Язык: Английский
Процитировано
7
Journal of Science, Management and Technology, Год журнала: 2024, Номер 5(2), С. 3 - 21
Опубликована: Май 9, 2024
A considerable number of published research has indicated that evaluating the success weightloss therapy involves proper dietary examination. On other hand, bulk evaluation methods currently in use have favored manual memory recall. In current study, we used an artificial neural network (ANN) machine learning algorithm to construct intelligencebased nutritional assessment system. The information from a user's regular meals as well their preexisting health indicators formulate based requirement. ANN-based approaches will make it possible assess eating habits, recommend daily meals, and improve general health. particular, develop technique identify multiple food items by classifying them using ANN identifying suitable assessments anthropometric, biochemical, clinical, (ABCD) data. Using model, intelligence system initially creates proposals input. Next, unique ABCD evaluation, feature maps for each proposal classify diet interval its composition. Lastly, UK-based Dietary Reference Values (DRVs) ranges basis, examined obtained results experiment shown our can reliably quickly provide reports, which give users clear understanding practical healthy recommendations strictly vegan diet.
Язык: Английский
Процитировано
1