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Research ArticleOriginal Article
Open Access

Acute coronary syndrome risk prediction of rapid emergency medicine scoring system in acute chest pain

An observational study of patients presenting with chest pain in the emergency department in Central Saudi Arabia

Tahir Mehmood, Mohammad S. Al Shehrani and Muhammad Ahmad
Saudi Medical Journal August 2017, 38 (9) 900-904; DOI: https://doi.org/10.15537/smj.2017.9.20809
Tahir Mehmood
From the Department of Emergency, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia
MRCS, FCPS
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  • For correspondence: [email protected]
Mohammad S. Al Shehrani
From the Department of Emergency, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia
MBBS
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Muhammad Ahmad
From the Department of Emergency, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia
MBBS, MRCP
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Article Information

vol. 38 no. 9 900-904
DOI 
https://doi.org/10.15537/smj.2017.9.20809
PubMed 
28889147

Published By 
Saudi Medical Journal
Online ISSN 
1658-3175
History 
  • Received March 8, 2017
  • Accepted May 31, 2017
  • Published online September 1, 2017.

Copyright & Usage 
Copyright: © Saudi Medical Journal This is an open-access article distributed under the terms of the Creative Commons Attribution-Noncommercial-Share Alike 3.0 Unported, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Author Information

  1. Tahir Mehmood, MRCS, FCPS⇑,
  2. Mohammad S. Al Shehrani, MBBS and
  3. Muhammad Ahmad, MBBS, MRCP
  1. From the Department of Emergency, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia
  1. Address correspondence and reprint request to: Dr. Tahir Mehmood, Department of Emergency, Prince Sultan Military Medical City, Riyadh, Kingdom of Saudi Arabia. E-mail: drtahirskt{at}yahoo.com ORCID: http://orcid.org/0000-0003-3926-0339
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  • An artificial intelligence approach to early predict non-ST-elevation myocardial infarction patients with chest pain
    Chieh-Chen Wu, Wen-Ding Hsu, Md. Mohaimenul Islam, Tahmina Nasrin Poly, Hsuan-Chia Yang, Phung-Anh  (Alex) Nguyen, Yao-Chin Wang, Yu-Chuan  (Jack) Li
    Computer Methods and Programs in Biomedicine 2019 173
  • Acute coronary syndrome prediction in emergency care: A machine learning approach
    Joshua Emakhu, Leslie Monplaisir, Celestine Aguwa, Suzan Arslanturk, Sara Masoud, Hashem Nassereddine, Mohamed S. Hamam, Joseph B. Miller
    Computer Methods and Programs in Biomedicine 2022 225
  • Combination of magnetic resonance imaging and targeted contrast agent for the diagnosis of myocardial infarction
    Jiangjun Qin, Shuchang Zhou, Zhiwei Li, Yinan Chen, Qun Qin, Tao Ai
    Experimental and Therapeutic Medicine 2018
  • Exception from informed consent for biomedical research in emergency settings: A study from Jordan
    Samah F. Al-Shatnawi, Karem H. Alzoubi, Rawand A. Khasawneh, Omar F. Khabour, Basima A. Almomani
    Heliyon 2021 7 12
  • Use of Wearable Technologies for Early Diagnosis and Management of Acute Coronary Syndromes and Arrhythmias
    Viet T. Le, Joseph B. Muhlestein
    Current Cardiovascular Risk Reports 2018 12 10
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Saudi Medical Journal: 38 (9)
Saudi Medical Journal
Vol. 38, Issue 9
1 Aug 2017
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Acute coronary syndrome risk prediction of rapid emergency medicine scoring system in acute chest pain
Tahir Mehmood, Mohammad S. Al Shehrani, Muhammad Ahmad
Saudi Medical Journal Aug 2017, 38 (9) 900-904; DOI: 10.15537/smj.2017.9.20809

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Acute coronary syndrome risk prediction of rapid emergency medicine scoring system in acute chest pain
Tahir Mehmood, Mohammad S. Al Shehrani, Muhammad Ahmad
Saudi Medical Journal Aug 2017, 38 (9) 900-904; DOI: 10.15537/smj.2017.9.20809
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© 2025 Saudi Medical Journal Saudi Medical Journal is copyright under the Berne Convention and the International Copyright Convention.  Saudi Medical Journal is an Open Access journal and articles published are distributed under the terms of the Creative Commons Attribution-NonCommercial License (CC BY-NC). Readers may copy, distribute, and display the work for non-commercial purposes with the proper citation of the original work. Electronic ISSN 1658-3175. Print ISSN 0379-5284.

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