Seyed Ehsan Saffari, Yilin Ning, Feng Xie, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Marcus Eng Hock Ong, Nan Liu 0003. AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes. In AMIA 2022, American Medical Informatics Association Annual Symposium, Washington, DC, USA, November 5-9, 2022. AMIA, 2022. [doi]
@inproceedings{SaffariNXCVVO022,
title = {AutoScore-Ordinal: An Interpretable Machine Learning Framework for Generating Scoring Models for Ordinal Outcomes},
author = {Seyed Ehsan Saffari and Yilin Ning and Feng Xie and Bibhas Chakraborty and Victor Volovici and Roger Vaughan and Marcus Eng Hock Ong and Nan Liu 0003},
year = {2022},
url = {https://knowledge.amia.org/76677-amia-1.4637602/f008-1.4640715/f008-1.4640716/285-1.4640981/357-1.4640978},
researchr = {https://researchr.org/publication/SaffariNXCVVO022},
cites = {0},
citedby = {0},
booktitle = {AMIA 2022, American Medical Informatics Association Annual Symposium, Washington, DC, USA, November 5-9, 2022},
publisher = {AMIA},
}