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. 2024 Oct 4:7:1422551.
doi: 10.3389/frai.2024.1422551. eCollection 2024.

Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis

Jithin K Sreedharan  1 , Fred Saleh  2 , Abdullah Alqahtani  3 , Ibrahim Ahmed Albalawi  3 , Gokul Krishna Gopalakrishnan  4 , Hadi Abdullah Alahmed  5 , Basem Ahmed Alsultan  5 , Dhafer Mana Alalharith  5 , Musallam Alnasser  3 , Ayedh Dafer Alahmari  6 , Manjush Karthika  7
Affiliations

Applications of artificial intelligence in emergency and critical care diagnostics: a systematic review and meta-analysis

Jithin K Sreedharan et al. Front Artif Intell. .

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; critical care medicine; diagnosis; healthcare; machine learning.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Assessment of quality of selected studies using QUADAS-2 (graph plot).
Figure 2
Figure 2
Assessment of quality of selected studies using QUADAS-2 (summary plot).
Figure 3
Figure 3
PRISMA flowchart depicting the flow of selection of studies.
Figure 4
Figure 4
Accuracy of AI diagnosis in Barrette’s neoplasia (forest plot).
Figure 5
Figure 5
Accuracy of AI diagnosis in Barrette’s neoplasia (SROC plot).
Figure 6
Figure 6
Accuracy of AI diagnosis in gastrointestinal stromal tumor (forest plot).
Figure 7
Figure 7
Accuracy of AI diagnosis in gastrointestinal stromal tumor (SROC plot).
Figure 8
Figure 8
Accuracy of AI diagnosis in esophageal adenocarcinoma (forest plot).
Figure 9
Figure 9
Accuracy of AI diagnosis in esophageal adenocarcinoma (SROC plot).
See this image and copyright information in PMC

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