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

Automatic Processing and Automatic Social Behavior01:28

Automatic Processing and Automatic Social Behavior

378
Automatic processing refers to the cognitive operations that occur without conscious intent or awareness, playing a fundamental role in shaping social cognition and behavior. These processes enable individuals to navigate complex social environments efficiently by relying on mental shortcuts and pre-existing knowledge structures known as schemas. One of the most influential mechanisms underlying automatic processing is priming, which subtly activates mental representations through exposure to...
378
Cognitive Therapy01:25

Cognitive Therapy

1.6K
Cognitive therapy, pioneered by Aaron T. Beck in the 1960s, is a structured approach to addressing psychological distress by focusing on the influence of thoughts on emotions and behaviors. All cognitive therapies involve the basic assumption that human beings have control over their feelings, and that how individuals feel about something depends on how they think about it. Unlike psychoanalytic methods that delve into unconscious processes or humanistic approaches emphasizing...
1.6K
Treatment Strategies for Psychological Disorders01:24

Treatment Strategies for Psychological Disorders

1.0K
Treatment approaches for psychological disorders fall into three main categories: psychological, biological, and sociocultural. Each approach targets different aspects of mental health, requiring varying levels of education and training.
Psychological therapies focus on modifying emotions, thoughts, and behaviors through talking, interpreting, listening, rewarding, challenging, and modeling. Clinical psychologists, counselors, and social workers commonly practice psychotherapy. Clinical...
1.0K
Natural and Artificial Concepts01:24

Natural and Artificial Concepts

747
In psychology, concepts can be divided into two categories: natural and artificial. Natural concepts are formed through direct or indirect experiences. For example, consider the concept of snow. If you live in a place with regular snowfall, such as Essex Junction, Vermont, you know snow through direct experiences. You’ve seen it fall, touched it, shoveled it, and played in it. You recognize its texture, appearance, and even its smell. In contrast, if you live on an island like Saint...
747
Introduction to Cognitive Psychology01:20

Introduction to Cognitive Psychology

2.8K
Cognitive psychology is the field of psychology dedicated to examining how people think. It attempts to explain how and why we think the way we do by studying the interactions among human thinking, emotion, creativity, language, and problem-solving, as well as other cognitive processes. Cognitive psychology studies how information is processed and manipulated in remembering, thinking, and knowing.
This field emerged in the mid-20th century, following a period dominated by behaviorism, which...
2.8K
Reason and Intuition01:37

Reason and Intuition

5.9K
The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
5.9K

You might also read

Related Articles

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

Sort by
Same author

Correction: Comparative evaluation of deep learning models for lung segmentation in chest X-rays: applications in infectious disease screening.

BMC infectious diseases·2026
Same author

Ending Lassa neglect: the urgent case for a licensed vaccine.

Annals of medicine and surgery (2012)·2026
Same author

Rehab-DRLX: explainable neurorehabilitation prognosis using deep reinforcement learning and transformer-based models.

Frontiers in computational neuroscience·2026
Same author

Explainable Deep Learning Framework for Multimodal Brain Tumor Classification via Neuroimaging Attribute Extraction.

IEEE journal of biomedical and health informatics·2026
Same author

Optimized deep learning ensemble using Fast Osprey algorithm for accurate lymphoblastic leukemia detection.

Frontiers in medicine·2026
Same author

Optimized Machine Learning Pipeline for Lung Cancer Classification: Feature Reduction and Hyperparameter Tuning.

Diagnostics (Basel, Switzerland)·2026
Same journal

Big Data-Driven Video Anomaly Detection Using VideoMAE for Visual Analytics in CCTV Surveillance.

Big data·2026
Same journal

Agentic Artificial Intelligence-Driven Explainable Deep Learning for Deciphering Noncoding Pathogenic Mechanisms of Delirium Through Genomic Big Data Integration.

Big data·2026
Same journal

Personalized Driven Instruction Through Explainable Agentic AI in Multicultural Higher Education Environments.

Big data·2026
Same journal

Big Data-Driven Explainable Agentic AI Decision Frameworks for Enterprise Innovation in FinTech Ecosystems.

Big data·2026
Same journal

An Edge-Enabled Low-Latency Cross-Lingual Speech-to-Text Framework for Efficient Human-Robot Interaction.

Big data·2026
Same journal

DS<sup>2</sup>PT: A Deep Two-Stage Patent Text Segmentation Framework Informed by Low-Latency Neural Network Characteristics.

Big data·2026
See all related articles

Related Experiment Video

Updated: May 7, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

1.2K

ThinkAI: A Natural Language Processing-based Intelligent framework for Mental Health.

Kashish Ara Shakil1, Mudasir Ahmad Wani2, Faiz Ullah3

  • 1Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia.

Big Data
|May 6, 2026
PubMed
Summary
This summary is machine-generated.

ThinkAI uses natural language processing (NLP) to analyze journal entries, identifying emotional patterns and mental health changes. This AI tool combines classical and transformer models for accurate depression detection and emotion analysis, aiding well-being management.

Keywords:
BERTNLPRoBERTa and DistilRoBERTagenerative AImental health

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.4K

Related Experiment Videos

Last Updated: May 7, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
07:14

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models

Published on: December 23, 2025

1.2K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

8.4K

Area of Science:

  • Computational psychology
  • Artificial intelligence in mental health
  • Natural Language Processing (NLP)

Background:

  • Rising prevalence of emotional and mental health challenges in the digital age.
  • Need for innovative, accessible tools for emotional well-being support.
  • Limitations of traditional mental health monitoring methods.

Purpose of the Study:

  • Introduce ThinkAI, a platform for understanding and managing mental health through journaling.
  • Leverage NLP to analyze user-written text for emotional patterns and well-being trends.
  • Develop a technically validated and ethically grounded framework for real-time mental health monitoring.

Main Methods:

  • Utilized journaling as a secure, private input method for users.
  • Applied NLP algorithms, including classical machine learning and transformer-based models (BERT, RoBERTa, DistilRoBERTa).
  • Evaluated models for depression detection (Support Vector Machine, Naive Bayes) and emotion analysis.

Main Results:

  • Support Vector Machine achieved 0.920 accuracy and 0.97 ROC-AUC for depression detection.
  • Naive Bayes model demonstrated a recall of 0.947 for depression detection.
  • BERT model yielded 0.945 accuracy and 0.9446 F1-score for emotion analysis.

Conclusions:

  • Combining classical and transformer models offers powerful tools for mental health analysis.
  • ThinkAI provides visual insights and alerts, promoting self-awareness and timely intervention.
  • The framework supports real-time mental well-being monitoring, digital therapeutics, and psychological data analysis.