About OJO | Search | Ahead of print | Current Issue | Archives | Author Instructions | Reviewer Guidelines | Online submissionLogin 
Oman Journal of Ophthalmology Oman Journal of Ophthalmology
  Editorial Board | Subscribe | Advertise | Contact
https://www.omanophthalmicsociety.org/ Users Online: 961  Wide layoutNarrow layoutFull screen layout Home Print this page  Email this page Small font size Default font size Increase font size

 Table of Contents    
Year : 2021  |  Volume : 14  |  Issue : 3  |  Page : 203-204  

Artificial intelligence to predict ocular manifestation of COVID-19

1 Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India
2 Chitkara School of Health Sciences, Chitkara University, Rajpura, Punjab, India

Date of Submission14-Dec-2020
Date of Decision23-May-2021
Date of Acceptance24-May-2021
Date of Web Publication20-Oct-2021

Correspondence Address:
Nayan Gupta
Chitkara School of Health Sciences, Chitkara University, Rajpura, Punjab
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ojo.ojo_464_20

Rights and Permissions

How to cite this article:
Nagpal D, Gupta N. Artificial intelligence to predict ocular manifestation of COVID-19. Oman J Ophthalmol 2021;14:203-4

How to cite this URL:
Nagpal D, Gupta N. Artificial intelligence to predict ocular manifestation of COVID-19. Oman J Ophthalmol [serial online] 2021 [cited 2023 Mar 29];14:203-4. Available from: https://www.ojoonline.org/text.asp?2021/14/3/203/328610


The surge of coronavirus across the globe has enforced clinicians, health-care workers, scientists, and governments to work together to strategize the preventive measures against this pandemic. It is now established that coronavirus and its variants have various systemic association along with ocular manifestations. Various published literatures report ocular manifestations in the middle phase of the disease.[1],[2],[3] Most of these anterior segment signs such as conjunctival congestion, epiphora, and increased secretions due to coronavirus are reported among patients with severe pneumonia. Other ocular abnormalities presented in animal models include anterior uveitis, optic neuritis, and retinitis. These occurrences of the ocular symptoms may appear as the initial sign or during the spread of COVID-19. Mucormycosis is another sight-threatening sign reported among COVID patients.[4]

Important measures for a safe ophthalmic practice during this pandemic include various measures such as stratification of patients for clinical visits, protection of medical workers, surveillance of medical workers, sterilization, and diagnostic techniques. [Figure 1] illustrates the steps for safe ophthalmic practice.
Figure 1: Proposed methodology

Click here to view

Ocular symptoms can be diagnosed through varying imaging modalities for screening of COVID-19-related symptoms through computer-aided diagnosis. The collaboration between clinicians and health-care industry workers is a boon for diagnosing COVID-19 through artificial intelligence (AI) and machine learning (ML) techniques. Medical industries are engaged in the diagnosis and various AI applications that have been implemented for screening and providing decision support for clinicians, for diagnosing the disease with ease.

COVID-19 has the possibility to influence the retinal microvasculature. It can be recognized by taking the fundus images which includes various morphological changes present in the retina. These morphological changes can be distinguished either by tedious manual examination or by computer-aided diagnosis (CAD) that can assist the ophthalmologist with recognizing the issue. The flowchart of the proposed methodology is represented in [Figure 2].
Figure 2: Important considerations for safe ophthalmic practice

Click here to view

  • Data acquisition: data acquisition of COVID-19 patients can also be done by wearing protective shields along with necessary equipment for checking the retinal images
  • Region investigation of the existing approach: region investigation assumes a significant part in deciding any kind of sickness. The locale can likewise be indicated utilizing different highlights, for example, optic disc, blood vasculature, and so forth
  • Image preprocessing (IP): IP is a significant factor which influences the image quality. IP incorporates the handling of the picture by eliminating commotion, shading change for the detection of COVID-19
  • Image segmentation: segmentation of the region can be done by focusing on specific part of the region which shows significant changes in the retina. The changes that can be seen due to COVID-19 are neovascularization, presence of microaneurysms, hemorrhages, etc.
  • Feature extraction: feature extraction is an evaluative advance as the classifier will perceive yield from the information include design
  • Classification: the classification and grading can be done based on the presence of changes in retinal images
  • Performance evaluation: Assessment of the infection can be anticipated by different boundaries, for example, receiving operator curve, area under curve, sensitivity, specificity, and accuracy.

Hence, AI and ML through CAD are the recent advancements which should be considered for ophthalmic diagnostics.

Financial support and sponsorship


Conflicts of interest

There are no conflicts of interest.

   References Top

Seah I, Agrawal R. Can the coronavirus disease 2019 (COVID-19) affect the eyes? A review of coronaviruses and ocular implications in humans and animals. Ocul Immunol Inflamm 2020;28:391-5.  Back to cited text no. 1
Bertoli F, Veritti D, Danese C, Samassa F, Sarao V, Rassu N, et al. Ocular findings in COVID-19 patients: A review of direct manifestations and indirect effects on the eye. J Ophthalmol 2020;2020;4827304.  Back to cited text no. 2
Invernizzi A, Torre A, Parrulli S, Zicarelli F, Schiuma M, Colombo V, et al. Retinal findings in patients with COVID-19: Results from the SERPICO-19 study. EClinicalMedicine 2020;27:100550.  Back to cited text no. 3
Dyer O. Covid-19: India sees record deaths as “black fungus” spreads fear. Br Med J 2021;22:53.  Back to cited text no. 4


  [Figure 1], [Figure 2]


    Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
    Access Statistics
    Email Alert *
    Add to My List *
* Registration required (free)  

  In this article
    Article Figures

 Article Access Statistics
    PDF Downloaded82    
    Comments [Add]    

Recommend this journal