Applications of Machine Learning Approaches in Emergency Medicine; a Review Article.
Using artificial intelligence and machine learning techniques in different medical fields, especially emergency medicine is rapidly growing. In this paper, studies conducted in the recent years on using artificial intelligence in emergency medicine have been collected and assessed. These studies bel...
| Publicado en: | Archives of Academic Emergency Medicine Vol. 7; no. 1; pp. 1 - 10 |
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| Autores principales: | , |
| Formato: | review tables/charts Journal Article |
| Publicado: |
Shahid Beheshti University of Medical Sciences
2019
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=150483311&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 150483311 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 26454904 MFMK jtl: Archives of Academic Emergency Medicine issn: 26454904 maglogo: N pubinfo: dt: 2019 vid: 7 iid: 1 pid: 87963 pub: Shahid Beheshti University of Medical Sciences artinfo: ui: 150483311 150483311 150483311 150483311 ppf: 1 ppct: 9 formats: fmt: @attributes: type: P tig: atl: Applications of Machine Learning Approaches in Emergency Medicine; a Review Article. aug: au: Shafaf, Negin Malek, Hamed affil: Faculty of Computer Science and Engineering, Shahid Beheshti University, Tehran, Iran sug: subj: Machine Learning Utilization Emergency Medicine Disease Surveillance Artificial Intelligence Triage Kidney Failure, Acute Influenza Urinary Tract Infections Sepsis Pulmonary Disease, Chronic Obstructive Asthma Appendicitis ab: Using artificial intelligence and machine learning techniques in different medical fields, especially emergency medicine is rapidly growing. In this paper, studies conducted in the recent years on using artificial intelligence in emergency medicine have been collected and assessed. These studies belonged to three categories: prediction and detection of disease; prediction of need for admission, discharge and also mortality; and machine learning based triage systems. In each of these categories, the most important studies have been chosen and accuracy and results of the algorithms have been briefly evaluated by mentioning machine learning techniques and used datasets. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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