Skip to main content

SYSTEMATIC REVIEW article

Front. Artif. Intell.
Sec. Medicine and Public Health
Volume 7 - 2024 | doi: 10.3389/frai.2024.1422551

Applications of Artificial Intelligence (AI) in Emergency and Critical Care Diagnostics: A Systematic Review and Meta-Analysis

Provisionally accepted
Jithin K. Sreedharan Jithin K. Sreedharan 1*Fred Saleh Fred Saleh 2Abdullah Alqahtani Abdullah Alqahtani 3Ibrahim A. Albalawi Ibrahim A. Albalawi 3Gokul K. Gopalakrishnan Gokul K. Gopalakrishnan 4Hadi A. Alahmed Hadi A. Alahmed 5Basem A. Alsultan Basem A. Alsultan 5Dhafer M. Alalharith Dhafer M. Alalharith 5Musallam Alnasser Musallam Alnasser 3Ayedh D. Alahmari Ayedh D. Alahmari 4Manjush Karthika Manjush Karthika 6
  • 1 University of Doha for Science and Technology, Doha, Qatar
  • 2 Deanship, College of Health Sciences, University of Doha for Science and Technology, Doha, Qatar
  • 3 Department of Respiratory Care, Prince Sultan Military College of Health Sciences, Dammam, Saudi Arabia
  • 4 Department of Respiratory Care, Batterjee Medical College, Jeddah, Saudi Arabia
  • 5 Department of Respiratory Therapy, Armed Forces Hospital,, Dhahran, Dammam, Saudi Arabia
  • 6 Faculty of Medical and Health Sciences, Liwa College, Abu Dhabi, Abu Dhabi, United Arab Emirates

The final, formatted version of the article will be published soon.

    ABSTRACT: Introduction: Artificial intelligence has come to be the highlight in almost all fields of science. It uses various models and algorithms to detect patterns and specific findings to diagnose a disease with utmost accuracy. With the increasing need for accurate and precise diagnosis of disease, employing artificial intelligence models and concepts in healthcare setup can be beneficial. Methodology: The search engines and databases employed in this study are PubMed, ScienceDirect and Medline. Studies published between 1st January 2013 to 1st February 2023 were included in this analysis. The selected articles were screened preliminarily using the Rayyan web tool, after which investigators screened the selected articles individually. The risk of bias for the selected studies was assessed using QUADAS-2 tool specially designed to test bias among studies related to diagnostic test reviews. Results: In this review, 17 studies were included from a total of 12,173 studies. These studies were analysed for their sensitivity, accuracy, positive predictive value, specificity and negative predictive value in diagnosing barrette’s neoplasia, cardiac arrest, esophageal adenocarcinoma, sepsis and gastrointestinal stromal tumors. All the studies reported heterogeneity with p value < 0.05 at confidence interval 95%. Conclusion: The existing evidential data suggests that artificial intelligence can be highly helpful in the field of diagnosis providing maximum precision and early detection. This helps to prevent disease progression and also helps to provide treatment at the earliest. Employing artificial intelligence in diagnosis will define the advancement of health care environment and also be beneficial in every aspect concerned with treatment to illnesses.

    Keywords: artificial intelligence, machine learning, critical care medicine, healthcare, diagnosis

    Received: 24 Apr 2024; Accepted: 23 Sep 2024.

    Copyright: © 2024 Sreedharan, Saleh, Alqahtani, Albalawi, Gopalakrishnan, Alahmed, Alsultan, Alalharith, Alnasser, Alahmari and Karthika. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jithin K. Sreedharan, University of Doha for Science and Technology, Doha, Qatar

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.