Next Article in Journal
A Similarity Measure-Based Approach Using RS-fMRI Data for Autism Spectrum Disorder Diagnosis
Next Article in Special Issue
Suboptimal Chest Radiography and Artificial Intelligence: The Problem and the Solution
Previous Article in Journal
Muscle Cross-Sectional Area Segmentation in Transverse Ultrasound Images Using Vision Transformers
Previous Article in Special Issue
Double-Lumen Endotracheal Tube—Predicting Insertion Depth and Tube Size Based on Patient’s Chest X-ray Image Data and 4 Other Body Parameters
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diagnostics
Volume 13
Issue 2
10.3390/diagnostics13020216
diagnostics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?

by
Giovanni Irmici
1,
Maurizio Cè
1,
Elena Caloro
1,
Natallia Khenkina
1,
Gianmarco Della Pepa
1,
Velio Ascenti
1,
Carlo Martinenghi
2,
Sergio Papa
3,
Giancarlo Oliva
4 and
Michaela Cellina
4,*
1
Postgraduation School in Radiodiagnostics, Università degli Studi di Milano, Via Festa del Perdono, 7, 20122 Milan, Italy
2
Radiology Department, San Raffaele Hospital, Via Olgettina 60, 20132 Milan, Italy
3
Unit of Diagnostic Imaging and Stereotactic Radiosurgery, Centro Diagnostico Italiano, Via Saint Bon 20, 20147 Milan, Italy
4
Radiology Department, Fatebenefratelli Hospital, ASST Fatebenefratelli Sacco, Milano, Piazza Principessa Clotilde 3, 20121 Milan, Italy
*
Author to whom correspondence should be addressed.
Diagnostics 2023, 13(2), 216; https://doi.org/10.3390/diagnostics13020216
Submission received: 10 December 2022 / Revised: 28 December 2022 / Accepted: 3 January 2023 / Published: 6 January 2023
(This article belongs to the Special Issue Chest X-ray Detection and Classification of Chest Abnormalities)
Browse Figure
Review Reports Versions Notes

Abstract

Due to its widespread availability, low cost, feasibility at the patient’s bedside and accessibility even in low-resource settings, chest X-ray is one of the most requested examinations in radiology departments. Whilst it provides essential information on thoracic pathology, it can be difficult to interpret and is prone to diagnostic errors, particularly in the emergency setting. The increasing availability of large chest X-ray datasets has allowed the development of reliable Artificial Intelligence (AI) tools to help radiologists in everyday clinical practice. AI integration into the diagnostic workflow would benefit patients, radiologists, and healthcare systems in terms of improved and standardized reporting accuracy, quicker diagnosis, more efficient management, and appropriateness of the therapy. This review article aims to provide an overview of the applications of AI for chest X-rays in the emergency setting, emphasizing the detection and evaluation of pneumothorax, pneumonia, heart failure, and pleural effusion.
Keywords: artificial intelligence; chest X-ray; emergency radiology; deep learning; chest radiography artificial intelligence; chest X-ray; emergency radiology; deep learning; chest radiography

Share and Cite

MDPI and ACS Style

Irmici, G.; Cè, M.; Caloro, E.; Khenkina, N.; Della Pepa, G.; Ascenti, V.; Martinenghi, C.; Papa, S.; Oliva, G.; Cellina, M. Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available? Diagnostics 2023, 13, 216. https://doi.org/10.3390/diagnostics13020216

AMA Style

Irmici G, Cè M, Caloro E, Khenkina N, Della Pepa G, Ascenti V, Martinenghi C, Papa S, Oliva G, Cellina M. Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available? Diagnostics. 2023; 13(2):216. https://doi.org/10.3390/diagnostics13020216

Chicago/Turabian Style

Irmici, Giovanni, Maurizio Cè, Elena Caloro, Natallia Khenkina, Gianmarco Della Pepa, Velio Ascenti, Carlo Martinenghi, Sergio Papa, Giancarlo Oliva, and Michaela Cellina. 2023. "Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available?" Diagnostics 13, no. 2: 216. https://doi.org/10.3390/diagnostics13020216

APA Style

Irmici, G., Cè, M., Caloro, E., Khenkina, N., Della Pepa, G., Ascenti, V., Martinenghi, C., Papa, S., Oliva, G., & Cellina, M. (2023). Chest X-ray in Emergency Radiology: What Artificial Intelligence Applications Are Available? Diagnostics, 13(2), 216. https://doi.org/10.3390/diagnostics13020216

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop