"AutoScore-Imbalance: An interpretable machine learning tool for ..."

Han Yuan et al. (2022)

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DOI: 10.1016/J.JBI.2022.104072

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type: Journal Article

metadata version: 2024-08-16

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Han Yuan, Feng Xie, Marcus Eng Hock Ong, Yilin Ning, Marcel Lucas Chee, Seyed Ehsan Saffari, Hairil Rizal Abdullah, Benjamin Alan Goldstein, Bibhas Chakraborty, Nan Liu:
AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. J. Biomed. Informatics 129: 104072 (2022)

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