MindPulse: Employee Mental Health Detection and Attrition Prediction App

—Employee mental health problems and excessive turnover are challenges that impact organizations at levels beyond work quality, including productivity, workforce stability, and overall morale. Conventional methods tend to be ineffective in pre-emptively predicting and managing these problems with any consistency because there are no accurate predictive tools available. MindPulse is a machine learning (ML) and natural language processing (NLP) application that uses AI to analyze the well-being of employees and attrition risk. With BERT-based sentiment analysis, it analyzes social media information to identify initial indicators of mental distress, and gradient boosting models analyze employee-specific metrics t o forecast a ttrition patterns, By combining these insights, MindPulse allows organizations to make timely interventions, creating a healthier workplace and minimizing turnover. This new methodology improves workforce retention efforts by delivering actionable, data-driven insights, making it an essential tool for contemporary businesses.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-05-23
DOI
https://doi.org/10.5281/zenodo.15578443
Primary Topic
Mathematics and Applications
Type
article
Field-Weighted Citation Impact
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article

MindPulse: Employee Mental Health Detection and Attrition Prediction App

Zenodo (CERN European Organization for Nuclear Research)
Mathematics and Applications
article

MindPulse: Employee Mental Health Detection and Attrition Prediction App

article en

Abstract

—Employee mental health problems and excessive turnover are challenges that impact organizations at levels beyond work quality, including productivity, workforce stability, and overall morale. Conventional methods tend to be ineffective in pre-emptively predicting and managing these problems with any consistency because there are no accurate predictive tools available. MindPulse is a machine learning (ML) and natural language processing (NLP) application that uses AI to analyze the well-being of employees and attrition risk. With BERT-based sentiment analysis, it analyzes social media information to identify initial indicators of mental distress, and gradient boosting models analyze employee-specific metrics t o forecast a ttrition patterns, By combining these insights, MindPulse allows organizations to make timely interventions, creating a healthier workplace and minimizing turnover. This new methodology improves workforce retention efforts by delivering actionable, data-driven insights, making it an essential tool for contemporary businesses.

Zenodo (CERN European Organization for Nuclear Research)
Amal Jyothi College of Engineering
Decent work and economic growth
Openalex Percentile: Top 49%
Mathematics and Applications
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MindPulse: Employee Mental Health Detection and Attrition Prediction App · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS