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A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes
The AutoScore framework can automatically generate data-driven clinical scores in various clinical applications. Here, we present a protocol for developing clinical scoring systems for binary, survival, and ordinal outcomes using the open-source AutoScore package. We describe steps for package insta...
Autores principales: | Xie, Feng, Ning, Yilin, Liu, Mingxuan, Li, Siqi, Saffari, Seyed Ehsan, Yuan, Han, Volovici, Victor, Ting, Daniel Shu Wei, Goldstein, Benjamin Alan, Ong, Marcus Eng Hock, Vaughan, Roger, Chakraborty, Bibhas, Liu, Nan |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10200969/ https://www.ncbi.nlm.nih.gov/pubmed/37178115 http://dx.doi.org/10.1016/j.xpro.2023.102302 |
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