ML-Based Burnout Prediction System

BurnoutShield

AI-Powered Burnout Risk Prediction System

BurnoutShield is a Machine Learning-based burnout risk prediction system that helps users detect burnout risk early, based on 33 assessment variables covering demographic, work, lifestyle, and psychological indicator data.

33
Assessment Variables
4
Risk Levels
ML
Logistic Regression
Phenomenon

Why Burnout Should Not Be Ignored?

Burnout has become a global health crisis. WHO classifies burnout as an occupational phenomenon affecting millions of workers worldwide.

Burnout Onset

Physical & mental exhaustion

Chronic Stress

Constant work pressure

Declining Productivity

Performance & motivation drop

Mental Health Issues

Anxiety & depression

Depression Risk

Drastic decline in quality of life

The longer it goes unaddressed, the worse the impact
Classification

4 Burnout Risk Tiers

Based on research findings, burnout risk is classified into 4 levels using a Logistic Regression model.

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Level 1

Low

Shows no significant burnout symptoms. Mental and physical condition remains good.

Low Risk
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Level 2

Moderate

Beginning to show early burnout symptoms. Requires attention and better stress management.

Moderate Risk
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Level 3

High

Burnout symptoms are fairly severe. Prompt intervention and counseling are strongly recommended.

High Risk
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Level 4

Severe

Burnout condition is very severe and requires immediate professional care from a psychologist or psychiatrist.

Very High Risk
Features

Key Features of BurnoutShield

A comprehensive burnout prediction system combining Machine Learning, AI, and calendar integration.

Dashboard Analytics

Real-time visualization of burnout prediction results and user statistics. Track burnout risk trends with interactive charts and comprehensive reports.

33 Assessment Variables

The assessment consists of 33 variables covering demographic, work, and lifestyle data, along with psychological indicators (PHQ-9, GAD-7, Stress Score).

Machine Learning

Predicts burnout risk using a Logistic Regression algorithm trained on tech-industry datasets.

Gemini AI Recommendation

Provides personalized AI-based recommendations from Google Gemini, based on burnout prediction results for each user.

Google Calendar Integration

AI recommendations can be synced to Google Calendar as daily routine reminders to support mental health and work-life balance.

Guide

How to Use BurnoutShield

Follow these simple steps to start early detection of burnout risk.

Step 1

Login

Create an account & sign in

Step 2

Complete Profile

Demographic & work data

Step 3

33 Assessment

Fill out the full questionnaire

Step 4

Burnout Prediction

4-level risk result

Step 5

AI Recommendation

Personalized recommendations

Step 6

Sync Calendar

Daily routine schedule

Preview

Dashboard Preview

An intuitive interface to monitor and manage mental wellbeing.

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Online
U
Dashboard
Assessment
History
Calendar
Risk Level
Moderate
PHQ-9
12
GAD-7
8
Stress
65
Risk Trend Last 6 assessments
AI Recommendation Gemini AI

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Contact

Contact Us

If you have any questions, suggestions, or need help, feel free to reach out to us.