Skip to main content
User Image

أ.د. أحمد البراك

Professor

أستاذ في كلية الطب, رئيس وحدة المعلوماتية الطبية و التعليم الالكتروني. المشرف على كرسي المعلوماتية الصحية و تعزيز الصحة. رئيس البرنامج المشترك للصحة العامة في جامعة الملك سعود

كلية الطب
جامعة الملك سعود, كلية الطب, الدور الثاني مكاتب اعضاء هيئة التدريس 28235

Identifying Preventable Emergency Admissions in Hospitals Using Machine Learning

AI in emergency Medicine f

Abstract. Overcrowding in EDs has been viewed globally as a chronic health
challenge. It is directly related to the increased use of EDs for non-urgent issues,
leading to increased complications, long waiting times, a higher death rate, or
delayed intervention of those more acutely ill. This study aims to develop Machine
Learning models to differentiate immediate medical needs from unnecessary ED
visits. A Decision Tree, Random Forest, AdaBoost, and XGBoost models were built
and evaluated on real-life data. XGBoost achieved the best accuracy and F1-score.

Publisher Name
IOS
Publishing City
Italy
more of publication
publications

Abstract. Overcrowding in EDs has been viewed globally as a chronic health
challenge. It is directly related to the increased use of EDs for non-urgent issues,
leading to increased…

by Sarah A. ALKHODAIRa,1, Norah ALTWAIJRI a and Ahmed I. ALBARRAK
2023
Published in:
IOS
publications

Objective

by Nasriah Zakaria, Ohoud AlFakhry, Abeer Matbuli, Asma Alzahrani, Noha Samir Sadiq Arab, Alaa Madani, Noura Alshehri, Ahmed I Albarrak
2018
Published in:
Oxford press
publications

Background
Blood donation saves lives, and the communication between blood centers and donors plays a vital role in this. Smart apps are now considered an important communication tool, and…

by Afaf Ali Batis , Ahmed Albarrak
2021
Published in:
ScienceDirect