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

Binge Eating Disorders01:23

Binge Eating Disorders

325
Binge eating disorder is a significant mental health condition characterized by recurrent episodes of excessive food consumption within a short period, accompanied by a perceived loss of control over eating behavior. Unlike occasional overeating, binge eating disorder is marked by distressing emotions such as guilt, shame, and anxiety following binge episodes. The disorder affects individuals across different ages and backgrounds, with profound implications for physical and psychological...
325
Bulimia Nervosa01:30

Bulimia Nervosa

512
Bulimia nervosa is a complex and severe eating disorder characterized by a cyclical pattern of binge-and-purge eating pattern. It generally involves an episode of binge eating, followed by compensatory behaviors such as vomiting, excessive exercise, laxative use, or fasting, to prevent weight gain. Despite often maintaining a normal weight, individuals with bulimia are intensely preoccupied with their body image and harbor an overwhelming fear of gaining weight. This can contribute to the...
512
Anorexia Nervosa01:28

Anorexia Nervosa

579
Anorexia nervosa is a complex and severe eating disorder characterized by an intense fear of weight gain, an unrelenting pursuit of thinness, and a distorted body image. It often leads to dangerously low body weight relative to an individual's age and height. This disorder is marked by significant physical and psychological consequences, making it one of the most life-threatening psychiatric illnesses.
Symptoms and Physical Effects
Individuals with anorexia nervosa commonly exhibit extreme...
579
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

387
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
387
Modeling in Therapy01:26

Modeling in Therapy

272
Modeling, a key technique in therapy, uses observational learning to help clients acquire and practice new skills by watching therapists demonstrate desired behaviors. This approach, rooted in Albert Bandura's concept of vicarious learning, plays a significant role in therapeutic interventions for various psychological conditions, including social anxiety, ADHD, and depression.
Participant Modeling
Participant modeling involves therapists demonstrating calm and effective behaviors in...
272
Theoretical Approaches to Psychological Disorder01:29

Theoretical Approaches to Psychological Disorder

501
The development of psychological disorders, which are characterized by deviant, maladaptive, and personally distressing behaviors, has been explored through several theoretical approaches.
Biological approach
The biological approach posits that internal, organic factors are the primary causes of such disorders. This perspective emphasizes brain structure and function, genetic predispositions, and neurotransmitter imbalances. For example, schizophrenia has been associated with both genetic...
501

You might also read

Related Articles

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

Sort by
Same author

ACCELERATE-BASSO: early experiences and emerging best practices for ontology development in behavioral and social science research.

Journal of biomedical semantics·2026
Same author

Develop and validate a fair machine learning model to identify patients with high data-continuity in electronic health records data.

JAMIA open·2026
Same author

Build fair machine learning models to predict adverse outcomes for heart failure patients with preserved ejection fraction and with reduced ejection fraction.

JAMIA open·2026
Same author

Let large language models judge each other: multi-agent peer-reviewed reasoning for medical question answering.

Journal of the American Medical Informatics Association : JAMIA·2026
Same author

Assessing the quality of electronic health record data and the claims linked data for target trial emulation studies.

JAMIA open·2026
Same author

Agentic Authoring of OMOP Concept Sets from Natural Language.

medRxiv : the preprint server for health sciences·2026

Related Experiment Video

Updated: Dec 3, 2025

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

4.2K

Exploring Eating Disorder Topics on Twitter: Machine Learning Approach.

Sicheng Zhou1, Yunpeng Zhao2, Jiang Bian2

  • 1Institute for Health Informatics, University of Minnesota, Minneapolis, MN, United States.

JMIR Medical Informatics
|October 30, 2020
PubMed
Summary

A new CNN-LSTM classifier efficiently identifies eating disorder (ED) tweets, revealing key topics discussed by the public. This computational approach enhances understanding of these mental illnesses on social media.

Keywords:
eating disorderspublic healthsocial mediatext classificationtopic modeling

More Related Videos

Control of Eating Behavior Using a Novel Feedback System
04:48

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

11.4K
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

6.1K

Related Experiment Videos

Last Updated: Dec 3, 2025

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis
04:19

A Computer-Based Platform for Aiding Clinicians in Eating Disorder Analysis and Diagnosis

Published on: May 10, 2022

4.2K
Control of Eating Behavior Using a Novel Feedback System
04:48

Control of Eating Behavior Using a Novel Feedback System

Published on: May 8, 2018

11.4K
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

6.1K

Area of Science:

  • Computational psychiatry
  • Social media analytics
  • Natural Language Processing (NLP)

Background:

  • Eating disorders (EDs) are serious mental illnesses impacting mental and physical health.
  • Social media platforms like Twitter are valuable data sources for public health research.
  • Existing qualitative studies offer insights, but large-scale computational methods are needed to analyze ED discussions.

Purpose of the Study:

  • To develop and validate a machine learning classifier for identifying ED-related tweets.
  • To explore factors and topics associated with EDs using topic modeling.

Main Methods:

  • Collected and annotated 123,977 tweets using keywords.
  • Developed and evaluated supervised machine learning models (CNN-LSTM, SVM, Naïve Bayes).
  • Applied Correlation Explanation (CorEx) topic modeling to identified tweets and validated with manually curated rules.

Main Results:

  • A CNN-LSTM classifier achieved high performance (F1 scores of 0.89 and 0.90) for identifying laypeople's ED tweets.
  • Identified 40,790 ED-relevant tweets using the classifier.
  • CorEx identified 162 topics with a 77.07% coherence rate, reviewed by a domain expert.

Conclusions:

  • The CNN-LSTM classifier significantly improves efficiency over manual methods for identifying ED tweets.
  • Topic modeling revealed overlapping themes between machine learning and manual approaches.
  • Identified topics offer novel insights into understanding eating disorders.