Karthik Adapa, Malvika Pillai, Meagan Foster, Nadia Charguia, Lukasz Mazur. Using Explainable Supervised Machine Learning to Predict Burnout in Healthcare Professionals. In Brigitte Séroussi, Patrick Weber, Ferdinand Dhombres, Cyril Grouin, Jan-David Liebe, Sylvia Pelayo, Andrea Pinna 0001, Bastien Rance, Lucia Sacchi, Adrien Ugon, Arriel Benis, Parisis Gallos, editors, Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022, Medical Informatics Europe, Nice, France, May 27-30, 2022. Volume 294 of Studies in Health Technology and Informatics, pages 58-62, IOS Press, 2022. [doi]
@inproceedings{AdapaPFCM22,
title = {Using Explainable Supervised Machine Learning to Predict Burnout in Healthcare Professionals},
author = {Karthik Adapa and Malvika Pillai and Meagan Foster and Nadia Charguia and Lukasz Mazur},
year = {2022},
doi = {10.3233/SHTI220396},
url = {https://doi.org/10.3233/SHTI220396},
researchr = {https://researchr.org/publication/AdapaPFCM22},
cites = {0},
citedby = {0},
pages = {58-62},
booktitle = {Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022, Medical Informatics Europe, Nice, France, May 27-30, 2022},
editor = {Brigitte Séroussi and Patrick Weber and Ferdinand Dhombres and Cyril Grouin and Jan-David Liebe and Sylvia Pelayo and Andrea Pinna 0001 and Bastien Rance and Lucia Sacchi and Adrien Ugon and Arriel Benis and Parisis Gallos},
volume = {294},
series = {Studies in Health Technology and Informatics},
publisher = {IOS Press},
isbn = {978-1-64368-285-3},
}