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Related Concept Videos

Dietary Connections01:23

Dietary Connections

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In biological systems, most metabolic pathways are interconnected. The cellular respiration processes that convert glucose to ATP—such as glycolysis, pyruvate oxidation, and the citric acid cycle—tie into those that break down other organic compounds. As a result, various foods—from apples to cheese to guacamole—end up as ATP. In addition to carbohydrates, food also contains proteins and lipids—such as cholesterol and fats. All of these organic compounds are used...
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Assessment of the Gastrointestinal System II: Health Perception Pattern01:29

Assessment of the Gastrointestinal System II: Health Perception Pattern

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Assessing the gastrointestinal (GI) system is a complex process that begins with collecting subjective data. This data, collected through patient interviews, provides crucial insights into the patient's health history, perception patterns, and lifestyle habits, all contributing significantly to GI health.
Health Perception Patterns
Health perception patterns offer valuable insights into a patient's lifestyle habits and how they may impact their GI health. These patterns include:
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Related Experiment Video

Updated: Sep 28, 2025

Iterative Development of an Innovative Smartphone-Based Dietary Assessment Tool: Traqq
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Multimedia Data-Based Mobile Applications for Dietary Assessment.

Maria F Vasiloglou1, Isabel Marcano2, Sergio Lizama2

  • 1ARTORG Center for Biomedical Engineering Research, University of Bern, Bern, Switzerland.

Journal of Diabetes Science and Technology
|March 29, 2022
PubMed
Summary
This summary is machine-generated.

Smartphone AI can estimate nutrient intake in real-time, aiding diabetes mellitus (DM) and obesity management. Further research and user involvement are needed for clinical validation of these dietary assessment technologies.

Keywords:
AIappsdietary assessmentmHealthnutritionsmartphones

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Area of Science:

  • Biomedical Engineering
  • Nutritional Science
  • Artificial Intelligence in Healthcare

Background:

  • Diabetes mellitus (DM) and obesity are chronic diseases with high morbidity and mortality.
  • Accurate dietary assessment is crucial for managing DM and obesity, but current methods are error-prone, time-consuming, and costly.
  • Technological advancements in smartphones and AI enable real-time nutrient estimation from food images/videos.

Purpose of the Study:

  • To review image-based and video-based smartphone systems for dietary assessment.
  • To identify current technological capabilities and limitations in automated nutrient estimation.
  • To highlight areas for future research and development in dietary assessment technology.

Main Methods:

  • Systematic review of image-based and video-based dietary assessment systems.
  • Categorization of identified systems based on evaluation setting (laboratory, preclinical, clinical).
  • Analysis of technological approaches and reported performance of the systems.

Main Results:

  • Identified 22 distinct dietary assessment systems utilizing smartphone technology.
  • Systems were categorized into laboratory (12), preclinical (7), and clinical (3) settings.
  • Significant research questions and technical challenges remain, particularly regarding real-world validation and user integration.

Conclusions:

  • Smartphone-based AI offers promising real-time dietary assessment for chronic disease management.
  • Further research is needed to address technical challenges and validate systems in real-life conditions.
  • Involving healthcare professionals and patients in system design is essential for successful implementation.