Detection of Covid-19 Using AI Application

被引:0
|
作者
Kanna R.K. [1 ]
Ishaque M. [2 ]
Panigrahi B.S. [3 ]
Pattnaik C.R. [4 ]
机构
[1] Department of Biomedical Engineering, Vels Institute of Science Technology and Advanced Studies [VISTAS]
[2] Department of Computer Science and Information Technology, Jeddah International College
[3] Department of Computer Science & Engineering (AI&ML), Vardhaman College of Engineering (Autonomous)
[4] Department of Computer Science & Engineering, Ajay Binay Institute of Technology, Cuttack
关键词
Artificial Intelligence; Contagious; Corona virus; CT imaging; RT-PCR;
D O I
10.4108/eetpht.9.3349
中图分类号
学科分类号
摘要
INTRODUCTION: In December of 2019, the infection which caused the pandemic started in the Hubei territory of Wuhan, China. They were identified as SARS-CoV-2, a highly infectious, easily transmissible virus that has caused an increasing number of deaths worldwide. Covid can be perceived with a testing strategy known as RT-PCR. As of now, this technique is broadly utilized for identifying the infection. OBJECTIVES: The imaging modalities are utilized for various degrees of seriousness from asymptomatic to basic cases. Side effects of an individual contaminated with COVID-19 incorporate gentle hack, fever, chest torment, weakness, and so forth An individual with an extreme fundamentalailment requires basic consideration. Imaging has assumed a larger part during the flare-up, with CT being a betteroption than invert transcriptase-polymerase chain response testing. METHODS: With artificial intelligence and robotics, a variety of devices and solutions have been introduced to improve contactless service for humans. The presentationof AI technology may be a distinct advantage for the contactless treatment of patients. Information technology and AI could solve the testing and tracking system without any human interaction. RESULTS: CT imaging methods permit radiologists and doctors to distinguish inner structures and see their shape, size, thickness, and surface, which could help in the early discovery of asymptomatic cases. CONCLUSION: This detailed information data can be utilized to decide whether there's a clinical issue, provide the extent and accurate area of the matter, and uncover other significant details which will assist the doctor with deciding the best treatment. © 2023 R. Kishore Kanna et al.
引用
收藏
相关论文
共 50 条
  • [1] Using AI ethically to tackle covid-19
    Cave, Stephen
    Whittlestone, Jess
    Nyrup, Rune
    HEigeartaigh, Sean O.
    Calvo, Rafael A.
    BMJ-BRITISH MEDICAL JOURNAL, 2021, 372
  • [2] COVID-19 and AI
    Narayan, Mahesh
    CHEMICAL & ENGINEERING NEWS, 2021, 99 (37) : 3 - 3
  • [3] AI & COVID-19
    Bacciu, Davide
    Girardi, Emanuela
    Maratea, Marco
    Sousa, Jose
    INTELLIGENZA ARTIFICIALE, 2021, 15 (02) : 45 - 53
  • [4] An AI healthcare ecosystem framework for Covid-19 detection and forecasting using CronaSona
    Hassan, Samah A. Z.
    MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2024, 62 (07) : 1959 - 1979
  • [5] Perspective of AI system for COVID-19 detection using chest images: a review
    Dolly Das
    Saroj Kumar Biswas
    Sivaji Bandyopadhyay
    Multimedia Tools and Applications, 2022, 81 : 21471 - 21501
  • [6] Perspective of AI system for COVID-19 detection using chest images: a review
    Das, Dolly
    Biswas, Saroj Kumar
    Bandyopadhyay, Sivaji
    MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (15) : 21471 - 21501
  • [7] Contemporary Study for Detection of COVID-19 Using Machine Learning with Explainable AI
    Akbar, Saad
    Azam, Humera
    Almutairi, Sulaiman Sulmi
    Alqahtani, Omar
    Shah, Habib
    Aleryani, Aliya
    CMC-COMPUTERS MATERIALS & CONTINUA, 2024, 80 (01): : 1075 - 1104
  • [8] An architecture for COVID-19 analysis and detection using big data, AI, and data architectures
    Alghamdi, Ahmed Mohammed
    Al Shehri, Waleed A.
    Almalki, Jameel
    Jannah, Najlaa
    Alsubaei, Faisal S.
    PLOS ONE, 2024, 19 (08):
  • [9] A survey of COVID-19 detection and prediction approaches using mobile devices, AI, and telemedicine
    Shen, John
    Ghatti, Siddharth
    Levkov, Nate Ryan
    Shen, Haiying
    Sen, Tanmoy
    Rheuban, Karen
    Enfield, Kyle
    Facteau, Nikki Reyer
    Engel, Gina
    Dowdell, Kim
    FRONTIERS IN ARTIFICIAL INTELLIGENCE, 2022, 5
  • [10] AI Driven Solution for the Detection of COVID-19 Using X-ray images
    Singh, Riya
    Wadkar, Shivani
    Jain, Semil
    Dodeja, Manisha
    PROCEEDINGS OF 2021 13TH INTERNATIONAL CONFERENCE ON INFORMATION & COMMUNICATION TECHNOLOGY AND SYSTEM (ICTS), 2021, : 123 - 128