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Related Concept Videos

Obesity01:24

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The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Models of Health Promotion and Illness Prevention II01:18

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The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
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Updated: Jan 7, 2026

Multidisciplinary Approach to Obesity Management: A Case Report
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Multidisciplinary Approach to Obesity Management: A Case Report

Published on: May 30, 2025

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Artificial Intelligence in Obesity Prevention.

Golbarg Shabani Jafarabadi1, Luca Busetto2

  • 1Department of Agronomy Food Natural Resources Animals and Environment, University of Padova, 35128 Padova, Italy.

Healthcare (Basel, Switzerland)
|December 30, 2025
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) offers new methods for predicting obesity, a complex disorder linked to chronic diseases. AI tools, including machine learning, help identify patterns and improve early obesity detection and prevention strategies.

Keywords:
artificial intelligenceobesityobesity prediction

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Area of Science:

  • Medical Informatics
  • Public Health
  • Artificial Intelligence in Medicine

Background:

  • Obesity is a complex disorder linked to chronic diseases like cancer, diabetes, and cardiovascular disease.
  • Early identification and diagnosis of obesity are critical for managing associated health risks.
  • Traditional anthropometric measures are being complemented by advanced Artificial Intelligence (AI) prediction models.

Purpose of the Study:

  • To conduct a comprehensive analysis of research on the impact of AI in obesity prevention.
  • To explore AI's role in assessing and predicting obesity.
  • To identify trends and guide future AI applications in obesity research.

Main Methods:

  • A scoping study was performed using AI to analyze research databases (PubMed, Scopus, Web of Science, Google Scholar).
  • Data from February 2009 to July 2025 were compiled and analyzed.
  • Employed AI approaches were arranged to identify patterns and trends in obesity prediction.

Main Results:

  • AI models can identify significant obesity patterns and links between factors and weight outcomes.
  • Deep learning and machine learning (logistic regression, decision trees, neural networks) provide new insights for obesity prediction.
  • Chatbots can serve as valuable resources for clinical knowledge and policy development in obesity medicine.

Conclusions:

  • AI presents promising solutions for modern challenges in obesity prediction and detection.
  • Further research is needed to fully leverage AI's potential in obesity management.
  • AI enhances the understanding and application of data analytics in obesity research.