A study published in Discover Artificial Intelligence used logistic regression, random forest and support vector machine (SVM) to classify health care workers according to their level of psychosocial resilience, using information collected during the COVID-19 pandemic. The logistic regression model produced the most accurate results, with an accuracy of 75.6% and an area under the ROC curve of 0.816, outperforming random forest (72.6%) and support vector machine (70.8%).
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Machine Learning Model Accurately Assesses Psychological Resilience in Health Care Workers
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September 21, 2026
1 min read
📰 Medical Xpress
📋 Key Takeaway
A study published in Discover Artificial Intelligence developed a machine learning model to classify health care workers' psychosocial resilience during the COVID-19 pandemic, achieving 75.6% accuracy. This research is significant as it highlights the mental health challenges faced by health care workers in Iran and the potential for technology to assist in addressing these issues.
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