Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Models of Health Promotion and Illness Prevention I

Models of Health Promotion and Illness Prevention I

A model is a theoretical way to understand a concept or an idea. Models can overcome barriers to health regardless of diverse economic and cultural backgrounds. In addition, models make the task easier by providing different ways to approach complex issues. There are two major health promotion models: the health belief model and the health promotion model.
The health belief model (HBM) attempts to predict health-related behavior in specific belief patterns. According to the HBM, a person's...

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...

You might also read

Related Articles

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

Sort by

Same author

Lineage-specific chromatin poising enforced by ETS-IRF composite elements determines the divergent interferon responses of plasmacytoid dendritic cells and epithelial cells.

bioRxiv : the preprint server for biology·2026

Same author

Tomato leaf disease and severity prediction using multi-task learning.

BMC plant biology·2026

Same author

An ensemble of deep learning models with falcon optimization assisted diabetic retinopathy diagnosis on retinal fundus images.

Scientific reports·2026

Same author

Learning Occlusion-Dynamic Invariant Representations for Multi-Object Tracking.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

HierarchicalNets for multi level hierarchical classification of yoga poses.

Scientific reports·2026

Same author

Rose leaf disease classification and severity estimation using an interpretable vision transformer-based multi-task framework.

BMC plant biology·2026

Same journal

Integrated multi-assessment and structural performance index framework for stacking-sequence optimisation of natural fibre reinforced laminates.

Scientific reports·2026

Same journal

SuperiorGAT: graph attention networks for sparse LiDAR point cloud reconstruction in autonomous systems.

Scientific reports·2026

Same journal

The effect of stretching the pectoralis major, sternocleidomastoid, and iliopsoas muscles on 800 m swimming performance in master swimmers.

Scientific reports·2026

Same journal

ISNR-PQC: isometry noise resilience post quantum cryptography primitive.

Scientific reports·2026

Same journal

Identification of high-yielding and stable genotypes of barley in the cold climate of Iran using AMMI and GGE biplot models.

Scientific reports·2026

Same journal

Bayesian negative binomial modelling of spatial and temporal patterns of road traffic deaths in Ghana.

Scientific reports·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 31, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Large language model empowered explainable and interpretable mental health analysis.

Supriya Bajpai¹, Gargi Mishra², Rachna Jain³

¹Indian Institute of Technology Bombay, IITB-Monash Research Academy, Mumbai, 400076, India.

Scientific Reports

|May 29, 2026

Summary

This summary is machine-generated.

InsightDep is a new AI model that detects depression on social media with explanations. It uses advanced language models to make results understandable for mental health professionals.

Keywords:

Explainable artificial intelligence Generative artificial intelligence Interpretable artificial intelligence Large language model Mental health analysis

Related Experiment Videos

Last Updated: May 31, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

Area of Science:

Artificial Intelligence
Computational Linguistics
Mental Health Technology

Background:

Growing concern over mental health expression on social media.
Limitations of traditional depression detection methods in providing clear explanations.
Need for interpretable AI in mental health analysis.

Purpose of the Study:

Introduce InsightDep, an explainable AI model for detecting depression on social media.
Enhance interpretability of AI-driven mental health analysis using Large Language Models (LLMs).
Facilitate practical application in therapeutic assessments by medical experts.

Main Methods:

Utilized a BERT model variant adapted for Twitter data analysis.
Implemented masked attention techniques for classification and explainability.
Integrated LLMs to translate complex model explanations into human-understandable formats.

Main Results:

InsightDep achieved high performance on Twitter and Reddit datasets (macro-F1/accuracy: 0.599/0.671 and 0.994/0.994).
Outperformed existing state-of-the-art methods like BERTweet, TwHIN-BERT, and DepRoBERTa.
Demonstrated effective translation of technical results into interpretable insights.

Conclusions:

InsightDep offers a novel, explainable approach to social media depression detection.
The methodology supports the development of morally aware digital mental health channels.
The system is designed for practical use by licensed medical professionals in therapeutic settings.