Elsevier eBooks, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Elsevier eBooks, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Methods in microbiology, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0BIO Web of Conferences, Год журнала: 2025, Номер 172, С. 02002 - 02002
Опубликована: Янв. 1, 2025
Individualized and accurate evaluation of nutrient intake is essential for good health. Disease prevention increased food security This article combines image analysis with quantum algorithms precise insights, introducing an advanced quantum-enhanced AI system. It designed to predict the nutritional content foods consumed. The system starts taking photos using a Convolutional Neural Network (CNN) processed by it has classification accuracy 91.87%. User-specific information such as age, weight, height, BMI are also used calculate individual needs. enables tailored dietary recommendations. Quantum Support Vector Machines (QSVM), (QNN), Reinforcement Learning (QRL). system's Leveraging (QRL) high prediction accuracies 90%, 92%, 93%, ensuring efficient in different foods. Integrating computer models will greatly improve predictive performance scalability. led advances bioengineering applications related personalized nutrition. proposed approach potential be widely applied health care. By helping personal nutrition planning supporting decision-making at granular level.
Язык: Английский
Процитировано
0Elsevier eBooks, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0