| Autor: |
Jithin K. Sreedharan, Fred Saleh, Abdullah Alqahtani, Ibrahim Ahmed Albalawi, Gokul Krishna Gopalakrishnan, Hadi Abdullah Alahmed, Basem Ahmed Alsultan, Dhafer Mana Alalharith, Musallam Alnasser, Ayedh Dafer Alahmari, Manjush Karthika |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Frontiers in Artificial Intelligence, Vol 7 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2624-8212 |
| DOI: |
10.3389/frai.2024.1422551 |
| Popis: |
IntroductionArtificial 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.MethodologyThe 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.ResultsIn 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 |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
