Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Assessment of the Gastrointestinal System II: Health Perception Pattern01:29

Assessment of the Gastrointestinal System II: Health Perception Pattern

399
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:
399
Assessment of the Gastrointestinal System I: Subjective Data01:17

Assessment of the Gastrointestinal System I: Subjective Data

553
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 History
The initial step in assessing the GI system is obtaining a comprehensive health history. This includes inquiring about the patient's history or presence of problems...
553
Dietary Connections01:23

Dietary Connections

61.2K
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...
61.2K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Hierarchies of evidence applied to lifestyle Medicine (HEALM): introduction of a strength-of-evidence approach based on a methodological systematic review.

BMC medical research methodology·2019
Same author

Pathways and mechanisms linking dietary components to cardiometabolic disease: thinking beyond calories.

Obesity reviews : an official journal of the International Association for the Study of Obesity·2018
Same author

Anabolic-Androgenic Steroid Use Among 1,010 College Men.

The Physician and sportsmedicine·2016
Same author

Tailoring dietary approaches for weight loss.

International journal of obesity supplements·2014
Same author

Perspective: Obesity is not a disease.

Nature·2014
Same author

Can we say what diet is best for health?

Annual review of public health·2014

Related Experiment Video

Updated: Dec 27, 2025

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
04:46

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

Published on: September 18, 2018

7.6K

Dietary assessment can be based on pattern recognition rather than recall.

D L Katz1, L Q Rhee1, C S Katz1

  • 1Diet ID, Inc, Detroit, MI, United States.

Medical Hypotheses
|March 5, 2020
PubMed
Summary

Objective diet quality is crucial for health but rarely measured. A new pattern recognition method offers a faster, scalable way to assess diet, potentially making it a routine vital sign.

More Related Videos

Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.8K
Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
06:21

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method

Published on: February 19, 2021

6.2K

Related Experiment Videos

Last Updated: Dec 27, 2025

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake
04:46

'Boden Food Plate': Novel Interactive Web-based Method for the Assessment of Dietary Intake

Published on: September 18, 2018

7.6K
Deep Neural Networks for Image-Based Dietary Assessment
13:19

Deep Neural Networks for Image-Based Dietary Assessment

Published on: March 13, 2021

9.8K
Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method
06:21

Concept Development and Use of an Automated Food Intake and Eating Behavior Assessment Method

Published on: February 19, 2021

6.2K

Area of Science:

  • Nutritional Science
  • Public Health
  • Health Informatics

Background:

  • Diet is a primary determinant of health and mortality, yet objective dietary quality is seldom measured.
  • Current dietary assessment methods (journaling, recall) are time-intensive and unreliable.
  • There's a critical need to integrate nutrition assessment into routine healthcare, like blood pressure monitoring.

Purpose of the Study:

  • To introduce and validate a novel, pattern recognition-based approach for dietary intake assessment.
  • To explore the potential of this method to overcome limitations of traditional dietary assessment tools.
  • To advocate for the routine measurement of dietary quality as a vital sign.

Main Methods:

  • Developed a system that assesses dietary intake by recognizing established dietary patterns.
  • Utilized a pattern recognition approach, reversing the traditional food-item-by-item data assembly.
  • Provisionally tested the developed system to evaluate its efficacy.

Main Results:

  • Preliminary results support the hypothesis that pattern recognition can effectively assess dietary intake.
  • The developed method demonstrates potential advantages in speed, efficiency, cost, and scalability.
  • The system shows promise for transforming dietary assessment into a user-friendly process.

Conclusions:

  • Dietary assessment can be revolutionized by leveraging pattern recognition for speed and scalability.
  • This approach could enable dietary quality to become a universally measured and managed vital sign.
  • The proposed method offers a practical solution for integrating nutrition into routine health monitoring.