<ul data-eligibleForWebStory="false"><li>Healthcare professionals, especially nurses, experience heightened stress levels, accentuated by the COVID-19 crisis.</li><li>A new study presents a novel ensemble machine learning framework for stress monitoring using wearable sensor data.</li><li>The framework addresses data challenges by utilizing a multimodal dataset and advanced ML models like Random Forest and XGBoost.</li><li>The research aims to enhance the development of real-time stress-monitoring systems for healthcare workers' well-being, with future directions including demographic diversity and edge-computing implementations.</li></ul>

Stress Monitoring in Healthcare: An Ensemble Machine Learning Framework Using Wearable Sensor Data

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