no code implementations • 7 Apr 2023 • Yilin Ning, Victor Volovici, Marcus Eng Hock Ong, Benjamin Alan Goldstein, Nan Liu
A prediction model is most useful if it generalizes beyond the development data with external validations, but to what extent should it generalize remains unclear.
no code implementations • 15 Oct 2022 • Mingxuan Liu, Siqi Li, Han Yuan, Marcus Eng Hock Ong, Yilin Ning, Feng Xie, Seyed Ehsan Saffari, Victor Volovici, Bibhas Chakraborty, Nan Liu
We found that model backbone(s) differed among data types as well as the imputation strategy.
1 code implementation • 17 Feb 2022 • Seyed Ehsan Saffari, Yilin Ning, Xie Feng, Bibhas Chakraborty, Victor Volovici, Roger Vaughan, Marcus Eng Hock Ong, Nan Liu
This study aims to expand the AutoScore framework to provide a tool for interpretable risk prediction for ordinal outcomes.