Going vegan with ChatGPT: Towards Designing LLMs for Personalized Lifestyle Changes

Machine Learning with Applications, Journal Year: 2025, Volume and Issue: unknown, P. 100659 - 100659

Published: April 1, 2025

Language: Английский

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Nutrigenomics and Personalized Diets - Tailoring Nutrition for Optimal Health

Applied Food Research, Journal Year: 2025, Volume and Issue: unknown, P. 100980 - 100980

Published: May 1, 2025

Language: Английский

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Enhancing Personalized Nutrition: Towards A Hybrid Intelligence Approach with LLM-Powered Meal Planning

Communications in computer and information science, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 19

Published: Jan. 1, 2025

Language: Английский

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Navigating nutrients: A scoping review on real-time food nutrition classification and recommendation systems

Computers in Biology and Medicine, Journal Year: 2025, Volume and Issue: 192, P. 110306 - 110306

Published: May 5, 2025

Language: Английский

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Mediterranean Diet: From Ancient Traditions to Modern Science—A Sustainable Way Towards Better Health, Wellness, Longevity, and Personalized Nutrition

Sustainability, Journal Year: 2025, Volume and Issue: 17(9), P. 4187 - 4187

Published: May 6, 2025

The Mediterranean Diet (MD), although not always called by this name, has emerged over centuries as a diet influenced diverse civilizations in the region, who blended local produce, traditions, and rituals with new ingredients customs introduced through trade, migrations, or occupations. Historically characterized mainly plant-based foods, olive oil, fish, moderate meat consumption, wine MD was also shaped holistic health principles advocated figures like Hippocrates, Plato Galen. Modern investigations, including Ancel Keys’ Seven Countries Study, confirmed its protective role against cardiovascular disease other chronic illnesses, while UNESCO’s designation of an Intangible Cultural Heritage highlights broader cultural significance. Today, faces challenges from globalization shifts modern lifestyles, advances personalized AI-driven nutrition, well specific public initiatives offer opportunities to preserve core tenets balance, sustainability, communal eating for future generations along many scientifically proven benefits associated lifestyle.

Language: Английский

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Differential Private Federated Transfer Learning for Mental Health Monitoring in Everyday Settings: A Case Study on Stress Detection

Published: July 15, 2024

Mental health conditions, prevalent across various demographics, necessitate efficient monitoring to mitigate their adverse impacts on life quality. The surge in data-driven methodologies for mental has underscored the importance of privacy-preserving techniques handling sensitive data. Despite strides federated learning monitoring, existing approaches struggle with vulnerabilities certain cyber-attacks and data insufficiency real-world applications. In this paper, we introduce a differential private transfer framework enhance privacy enrich sufficiency. To accomplish this, integrate two pivotal elements: (1) privacy, achieved by introducing noise into updates, (2) learning, employing pre-trained universal model adeptly address issues imbalance insufficiency. We evaluate case study stress detection, dataset physiological contextual from longitudinal study. Our finding show that proposed approach can attain 10% boost accuracy 21% enhancement recall, while ensuring protection.

Language: Английский

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DishAgent: Enhancing Dining Experiences through LLM-Based Smart Dishes

Published: Oct. 11, 2024

Language: Английский

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Foods: Trends, Fads, and Mind-Sets as Envisioned by AI Using LLMs (Large Language Models)

Acta Scientifci Nutritional Health, Journal Year: 2024, Volume and Issue: unknown, P. 82 - 89

Published: Aug. 1, 2024

This paper presents an approach to synthesizing mind-sets using artificial intelligence, LLMs (large language models).The focuses on a general treatment of food trends and fads.The presented here shows how intelligence can become the source information, synthesizer in spirit Mind Genomics end up being reporter writing press releases after projecting what will happen years come.The represents new way understand topic is meant for educational purposes where student or professional must come speed quickly even think might be next.

Language: Английский

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Automated Learning and Scheduling Assistant using LLM

Journal of Ubiquitous Computing and Communication Technologies, Journal Year: 2024, Volume and Issue: 6(3), P. 284 - 293

Published: Sept. 1, 2024

Large Language Models (LLMs) serve as the backbone of many AI applications, such automatic content generation, virtual assistant and more. It is also used in automating educational processes, scheduling students’ assessments managing teachers’ essential duties. The proposed study focuses on design development an Automated Learning Scheduling Assistant to facilitate tasks like conducting unit test, internal assessment, providing complete schedules students staff using LLM. system designed prompt engineering technique improve task automation efficiency. Retrieval-Augmented Generation (RAG) helps retrieving information decision making, test generation tasks. Data storage retrieval are supported by integration vector database. primary objective enhance process administrative teaching functions, a scalable solution for modern learning environment.

Language: Английский

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Unveiling the potential of large language models in transforming chronic disease management: A mixed-method systematic review (Preprint)

Published: Dec. 24, 2024

Accounting for nearly three-quarters of deaths worldwide, chronic diseases are a major global health burden. Large language models (LLMs) advanced artificial intelligence systems, possessing transformative potential to optimise disease management, yet robust evidence is lacking. To synthesise on the feasibility, opportunities, and challenges LLMs across management spectrum–from prevention screening, diagnosis, treatment, long-term care. Following PRISMA (Preferred Reporting Items Systematic Reviews Meta-Analysis) guidelines, eleven databases (Cochrane Central Register Controlled Trials, CINAHL, Embase, IEEE Xplore, Medline via Ovid, ProQuest Health & Medicine Collection, ScienceDirect, Scopus, Web Science Core China National Knowledge Internet, SinoMed) were searched 17 April 2024. Intervention simulation studies included if they examined in managing diseases. Narrative analysis with descriptive figures utilised study findings. Random-effects meta-analyses conducted assess pooled effect estimates LLM feasibility management. Twenty eligible examining general-purpose (n = 17) fine-tuned 3) diseases, including cancer, cardiovascular metabolic disorders. demonstrated spectrum by generating relevant, comprehensible, accurate recommendations (71%; 95% confidence interval [CI] 0.59, 0.83; I2 88.32%) having higher rates compared (odds ratio 2.89; CI 1.83, 4.58; 54.45%). facilitated equitable information access, increased patient awareness ailments, preventive measures, treatment options, promoted self-management behaviours lifestyle modification symptom coping. Additionally, compassionate emotional support, social connections, healthcare resource improve outcomes However, faced addressing privacy, language, cultural issues, undertaking tasks, diagnostic, medication, comorbidities personalised regimens real-time adjustments multiple modalities. transform at individual, social, levels, their direct application clinical settings still its infancy. A multifaced approach–incorporating data security, domain-specific model fine-tuning, multimodal integration, wearables–is crucial evolve into invaluable adjuncts professionals PROSPERO (CRD42024545412).

Language: Английский

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