A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes
Titel:
A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes
Auteur:
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