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

Machine Learning (1501) Clinical Information and Decision Making (1434) Data Science (278) Decision Support for Health Professionals (1210)

Published on in Vol 8, No 10 (2020): October

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/20324, first published .
Institution-Specific Machine Learning Models for Prehospital Assessment to Predict Hospital Admission: Prediction Model Development Study

Institution-Specific Machine Learning Models for Prehospital Assessment to Predict Hospital Admission: Prediction Model Development Study

Institution-Specific Machine Learning Models for Prehospital Assessment to Predict Hospital Admission: Prediction Model Development Study

Authors of this article:

Toru Shirakawa1, 2 Author Orcid Image ;   Tomohiro Sonoo2, 3 Author Orcid Image ;   Kentaro Ogura2, 4 Author Orcid Image ;   Ryo Fujimori2, 4 Author Orcid Image ;   Konan Hara2, 5 Author Orcid Image ;   Tadahiro Goto2, 6 Author Orcid Image ;   Hideki Hashimoto3 Author Orcid Image ;   Yuji Takahashi3 Author Orcid Image ;   Hiromu Naraba3 Author Orcid Image ;   Kensuke Nakamura3, 7 Author Orcid Image
Article Authors Cited by (8) Tweetations (12) Metrics

Journals

  1. Liu K, Kotani T, Nakamura K, Chihiro T, Morita Y, Ishii K, Fujizuka K, Yasumura D, Taniguchi D, Hamagami T, Shimojo N, Nitta M, Hongo T, Akieda K, Atsuo M, Kaneko T, Sakuda Y, Andoh K, Nagatomi A, Tanaka Y, Irie Y, Kamijo H, Hanazawa M, Kasugai D, Ayaka M, Oike K, Lefor A, Takahashi K, Katsukawa H, Ogura T. Effects of evidence-based ICU care on long-term outcomes of patients with sepsis or septic shock (ILOSS): protocol for a multicentre prospective observational cohort study in Japan. BMJ Open 2022;12(3):e054478 View
  2. Chang H, Cha W. Artificial intelligence decision points in an emergency department. Clinical and Experimental Emergency Medicine 2022;9(3):165 View
  3. Chee M, Chee M, Huang H, Mazzochi K, Taylor K, Wang H, Feng M, Ho A, Siddiqui F, Ong M, Liu N. Artificial intelligence and machine learning in prehospital emergency care: A scoping review. iScience 2023;26(8):107407 View
  4. Seo H, Ahn I, Gwon H, Kang H, Kim Y, Cho H, Choi H, Kim M, Han J, Kee G, Park S, Seo D, Jun T, Kim Y. Prediction of hospitalization and waiting time within 24 hours of emergency department patients with unstructured text data. Health Care Management Science 2024;27(1):114 View
  5. Lee S, Park H, Hwang J, Lee S, Han K, Kim W, Jeong J, Kang H, Kim A, Lee C, Kim S, Akman C. Machine Learning-Based Models for Prediction of Critical Illness at Community, Paramedic, and Hospital Stages. Emergency Medicine International 2023;2023:1 View
  6. Alghamdi A, Alshibani A, Binhotan M, Alsabani M, Alotaibi T, Alharbi R, Alabdali A. The Ability of Emergency Medical Service Staff to Predict Emergency Department Disposition: A Prospective Study. Journal of Multidisciplinary Healthcare 2023;Volume 16:2101 View
  7. Kim J. Data integration using information and communication technology for emergency medical services and systems. Clinical and Experimental Emergency Medicine 2023;10(2):129 View

Books/Policy Documents

  1. Stewart J, Goudie A, Lu J, Dwivedi G. AI in Clinical Medicine. View