Zobrazeno 1 - 10
of 856
pro vyhledávání: '"COVID-19 Detection"'
Autor:
Shabir Husssain, Muhammad Ayoub, Junaid Abdul Wahid, Akmal Khan, Amerah Alabrah, Gehad Abdullah Amran
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-19 (2024)
Abstract In response to the pressing requirement for precise and easily accessible COVID-19 detection methods, we present the Cough2COVID-19 framework, which is cost-effective, non-intrusive, and widely accessible. The conventional diagnostic methods
Externí odkaz:
https://doaj.org/article/6698fe3a9fb141a0a8a876e9dcf749a4
Publikováno v:
Frontiers in Big Data, Vol 7 (2024)
Externí odkaz:
https://doaj.org/article/19dac8a0e7c94d1294dae19dbaa4bd2c
Autor:
Rawia Ahmed, Praveen Kumar Reddy Maddikunta, Thippa Reddy Gadekallu, Naif Khalaf Alshammari, Fatma Ali Hendaoui
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
Externí odkaz:
https://doaj.org/article/1ddf1635d7a946d0bcbdd1cf65eaff27
Autor:
Zhenzhen Xie, James D. Morris, Jianmin Pan, Elizabeth A. Cooke, Saurin R. Sutaria, Dawn Balcom, Subathra Marimuthu, Leslie W. Parrish, Holly Aliesky, Justin J. Huang, Shesh N. Rai, Forest W. Arnold, Jiapeng Huang, Michael H. Nantz, Xiao-An Fu
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-9 (2024)
Abstract COVID-19 has caused a worldwide pandemic, creating an urgent need for early detection methods. Breath analysis has shown great potential as a non-invasive and rapid means for COVID-19 detection. The objective of this study is to detect patie
Externí odkaz:
https://doaj.org/article/5dcc2bc18c644b838fddf60dc2ea9cea
Publikováno v:
IEEE Access, Vol 12, Pp 155151-155167 (2024)
Bias or spurious correlations in image backgrounds can impact neural networks, causing shortcut learning (Clever Hans Effect) and hampering generalization to real-world data. ISNet, a recently introduced architecture, proposed the optimization of Lay
Externí odkaz:
https://doaj.org/article/6b2a9d1fe0b54cdd8da90a030cecffdc
Autor:
Rawia Ahmed, Praveen Kumar Reddy Maddikunta, Thippa Reddy Gadekallu, Naif Khalaf Alshammari, Fatma Ali Hendaoui
Publikováno v:
Frontiers in Medicine, Vol 11 (2024)
The rapid spread of COVID-19 pandemic across the world has not only disturbed the global economy but also raised the demand for accurate disease detection models. Although many studies have proposed effective solutions for the early detection and pre
Externí odkaz:
https://doaj.org/article/51035eca58954339a68e44551e17dd37
Publikováno v:
IJAIN (International Journal of Advances in Intelligent Informatics), Vol 9, Iss 3, Pp 524-536 (2023)
The significance of efficient and accurate diagnosis amidst the unique challenges posed by the COVID-19 pandemic underscores the urgency for innovative approaches. In response to these challenges, we propose a transfer learning-based approach using a
Externí odkaz:
https://doaj.org/article/9f9fbf2bb587484b91dd15b977409138
Autor:
Sara Saberi Moghadam Tehrani, Maral Zarvani, Paria Amiri, Zahra Ghods, Masoomeh Raoufi, Seyed Amir Ahmad Safavi-Naini, Amirali Soheili, Mohammad Gharib, Hamid Abbasi
Publikováno v:
BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-17 (2023)
Abstract Background Despite the globally reducing hospitalization rates and the much lower risks of Covid-19 mortality, accurate diagnosis of the infection stage and prediction of outcomes are clinically of interest. Advanced current technology can f
Externí odkaz:
https://doaj.org/article/b9fa8c3d67e74396bdebc990ac86c8e5
Autor:
Syed Thouheed Ahmed, Syed Muzamil Basha, Muthukumaran Venkatesan, Sandeep Kumar Mathivanan, Saurav Mallik, Najah Alsubaie, Mohammed S. Alqahtani
Publikováno v:
BMC Medical Imaging, Vol 23, Iss 1, Pp 1-10 (2023)
Abstract COVID-19, the global pandemic of twenty-first century, has caused major challenges and setbacks for researchers and medical infrastructure worldwide. The CoVID-19 influences on the patients respiratory system cause flooding of airways in the
Externí odkaz:
https://doaj.org/article/522d68a52a684b0881f63cd9c36cc9ac
Publikováno v:
Symmetry, Vol 16, Iss 7, p 870 (2024)
The challenges associated with conventional methods of COVID-19 detection have prompted the exploration of alternative approaches, including the analysis of lung X-ray images. This paper introduces a novel algorithm designed to identify abnormalities
Externí odkaz:
https://doaj.org/article/24bc6cd845e14c85983c802c30794724