Prediction of Depression in Techies at Workplaces
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-9228-5_12
Reference14 articles.
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3. S.-E. Cho, Z.W. Geem, K.-S. Na, Prediction of depression among medical check-ups of 433,190 patients: a nationwide population-based study. Psychiatry Res. 293, 113474 (2020). ISSN 0165-1781. https://doi.org/10.1016/j.psychres.2020.113474
4. L. Jena, N.K. Kamila, A model for prediction of human depression using apriori algorithm, in 2014 International Conference on Information Technology (Bhubaneswar, 2014), pp. 240–244. https://doi.org/10.1109/ICIT.2014.65
5. S.N. Kasthurirathne et al., Identification of patients in need of advanced care for depression using data extracted from a statewide health information exchange: a machine learning approach. J. Med. Int. Res. 21(7), e13809 (2019)
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