Department of Medical Informatics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
Stud Health Technol Inform. 2023 May 18;302:903-904. doi: 10.3233/SHTI230302.
Employees' mental health addresses concerns in the technology industry phenomenon. Machine Learning (ML) approaches show promise in predicting mental health problems and identifying related factors. This study used three machine learning models on OSMI 2019 dataset: MLP, SVM, and Decision Tree. Five features are extracted by permutation ML's method on the dataset. The results indicate that the models have been reasonably accurate. Moreover, they could effectively support predicting employee mental health comprehension in the technology industry.
员工的心理健康问题是科技行业关注的焦点。机器学习 (ML) 方法在预测心理健康问题和识别相关因素方面显示出了潜力。本研究使用了三种机器学习模型在 OSMI 2019 数据集上：MLP、SVM 和决策树。通过数据集的排列 ML 方法提取了五个特征。结果表明，这些模型具有相当的准确性。此外，它们可以有效地支持预测科技行业员工的心理健康状况。
