This paper is in the following e-collection/theme issue:

Machine Learning (1501) Clinical Information and Decision Making (1434) Decision Support for Health Professionals (1210) Innovations and Technology in Cancer Care (431) Infectious Diseases (non-STD/STI) (1592)

Published on in Vol 9, No 7 (2021): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/24651, first published .
Candidemia Risk Prediction (CanDETEC) Model for Patients With Malignancy: Model Development and Validation in a Single-Center Retrospective Study

Candidemia Risk Prediction (CanDETEC) Model for Patients With Malignancy: Model Development and Validation in a Single-Center Retrospective Study

Candidemia Risk Prediction (CanDETEC) Model for Patients With Malignancy: Model Development and Validation in a Single-Center Retrospective Study

Authors of this article:

Junsang Yoo1 Author Orcid Image ;   Si-Ho Kim2 Author Orcid Image ;   Sujeong Hur3, 4 Author Orcid Image ;   Juhyung Ha5 Author Orcid Image ;   Kyungmin Huh6 Author Orcid Image ;   Won Chul Cha4, 7, 8 Author Orcid Image
Article Authors Cited by (11) Tweetations (3) Metrics

Junsang Yoo   1 * , RN, PhD ;   Si-Ho Kim   2 * , MD ;   Sujeong Hur   3, 4 , RN, MS ;   Juhyung Ha   5 ;   Kyungmin Huh   6 , MD ;   Won Chul Cha   4, 7, 8 , MD

1 Department of Nursing, College of Nursing, Sahmyook University, Seoul, Republic of Korea

2 Division of Infectious Disease, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea

3 Department of Patient Experience Management, Samsung Medical Center, Seoul, Republic of Korea

4 Department of Digital Health, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Republic of Korea

5 Department of Computer Science, Indiana University Bloomington, Bloomington, IN, United States

6 Division of Infectious Disease, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

7 Department of Emergency Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea

8 Digital Innovation Center, Samsung Medical Center, Seoul, Republic of Korea

*these authors contributed equally

Corresponding Author:

  • Won Chul Cha, MD
  • Department of Emergency Medicine
  • Samsung Medical Center
  • Sungkyunkwan University School of Medicine
  • 81, Irwon-ro, Gangnam-gu
  • Seoul, 06351
  • Republic of Korea
  • Phone: 82 2-3410-2053
  • Email: wc.cha@samsung.com