TY - JOUR
T1 - COVID-19 detection by means of ECG, Voice, and X-ray computerized systems
T2 - a review
AU - Ribeiro, Pedro
AU - Marques, João Alexandre Lobo
AU - Rodrigues, Pedro Miguel
N1 - Funding Information:
This research was funded by National Funds from FCT—Fundação para a Ciência e a Tecnologia through projects UIDB/50016/2020.
Publisher Copyright:
© 2023 by the authors.
PY - 2023/2/3
Y1 - 2023/2/3
N2 - Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.
AB - Since the beginning of 2020, Coronavirus Disease 19 (COVID-19) has attracted the attention of the World Health Organization (WHO). This paper looks into the infection mechanism, patient symptoms, and laboratory diagnosis, followed by an extensive assessment of different technologies and computerized models (based on Electrocardiographic signals (ECG), Voice, and X-ray techniques) proposed as a diagnostic tool for the accurate detection of COVID-19. The found papers showed high accuracy rate results, ranging between 85.70% and 100%, and F1-Scores from 89.52% to 100%. With this state-of-the-art, we concluded that the models proposed for the detection of COVID-19 already have significant results, but the area still has room for improvement, given the vast symptomatology and the better comprehension of individuals’ evolution of the disease.
KW - Artificial intelligence
KW - Computerized diagnostic systems
KW - COVID-19
KW - Image processing
KW - Signal processing
UR - http://www.scopus.com/inward/record.url?scp=85149064284&partnerID=8YFLogxK
U2 - 10.3390/bioengineering10020198
DO - 10.3390/bioengineering10020198
M3 - Review article
C2 - 36829692
AN - SCOPUS:85149064284
SN - 2306-5354
VL - 10
JO - Bioengineering
JF - Bioengineering
IS - 2
M1 - 198
ER -
