Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions-Reference-Cited by-同舟云学术

Development and Assessment of an Interpretable Machine Learning Triage Tool for Estimating Mortality After Emergency Admissions

Published:2021-08-27 Issue:8 Volume:4 Page:e2118467
ISSN:2574-3805
Container-title:JAMA Network Open
language:en
Short-container-title:JAMA Netw Open

Author:

Xie Feng¹,Ong Marcus Eng Hock¹²,Liew Johannes Nathaniel Min Hui¹,Tan Kenneth Boon Kiat²,Ho Andrew Fu Wah¹²,Nadarajan Gayathri Devi²,Low Lian Leng¹³,Kwan Yu Heng¹⁴,Goldstein Benjamin Alan¹⁵,Matchar David Bruce¹⁶,Chakraborty Bibhas¹⁵⁷,Liu Nan¹⁸⁹

Affiliation:

1. Programme in Health Services and Systems Research, Duke–National University of Singapore Medical School, Singapore

2. Department of Emergency Medicine, Singapore General Hospital, Singapore

3. Department of Family Medicine and Continuing Care, Singapore General Hospital, Singapore

4. Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore

5. Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina

6. Duke University Medical Center, Duke University, Durham, North Carolina

7. Department of Statistics and Data Science, National University of Singapore, Singapore

8. Health Service Research Centre, Singapore Health Services, Singapore

9. Institute of Data Science, National University of Singapore, Singapore

Publisher

American Medical Association (AMA)

Subject

General Medicine

Link

https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2783549/xie_2021_oi_210545_1629491521.60927.pdf

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