1 Benchmarking Predictive Risk Models for Emergency Departments with Large Public Electronic Health Records Feng Xie 1# , Jun Zhou 2# , Jin Wee Lee 1 , Mingrui Tan 2 , Siqi Li 1 , Logasan S/O Rajnthern 3 , Marcel Lucas Chee 4 , Bibhas Chakraborty 1,5,6 , An-Kwok Ian Wong 7 , Alon Dagan 8,9 , Marcus Eng Hock Ong 1,10 , Fei Gao 2^ , Nan Liu 1,11,12^ * 1 Centre for Quantitative Medicine and Programme in Health Services and Systems Research, Duke-NUS Medical School, Singapore, Singapore 2 Institute of High Performance Computing, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore 3 School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore 4 Faculty of Medicine, Nursing and Health Sciences, Monash University, Victoria, Australia 5 Department of Statistics and Data Science, National University of Singapore, Singapore, Singapore 6 Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA 7 Division of Pulmonary, Allergy, and Critical Care Medicine, Duke University, Durham, NC, USA 8 Department of Emergency Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA 9 MIT Critical Data, Laboratory for Computational Physiology, Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, MA, USA 10 Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore 11 SingHealth AI Health Program, Singapore Health Services, Singapore, Singapore 12 Institute of Data Science, National University of Singapore, Singapore, Singapore # Joint first author ^ Joint last author * Correspondance: liu.nan@duke-nus.edu.sg