Home About us Editorial board Ahead of print Current issue Search Archives Submit article Instructions Subscribe Contacts Login 
  • Users Online: 4470
  • Home
  • Print this page
  • Email this page
Year : 2020  |  Volume : 68  |  Issue : 7  |  Page : 1339-1346

Insights into the growing popularity of artificial intelligence in ophthalmology

1 Department of Research & Development, Remidio Innovative Solutions, Bengaluru, Karnataka, India
2 Department of Artificial Intelligence, Medios Technologies, Singapore
3 Department of Ophthalmology, Dr. Mohan's Diabetes Specialities Centre Madras Diabetes Research Foundation, Chennai, Tamil Nadu, India

Correspondence Address:
Dr. Ramachandran Rajalakshmi
Department of Ophthalmology, Dr. Mohan's Diabetes Specialities Centre and Madras Diabetes Research Foundation, 6, Conran Smith Rd., Gopalapuram, Chennai - 600 086, Tamil Nadu
Login to access the Email id

Source of Support: None, Conflict of Interest: None

DOI: 10.4103/ijo.IJO_1754_19

Rights and Permissions

Artificial intelligence (AI) in healthcare is the use of computer-algorithms in analyzing complex medical data to detect associations and provide diagnostic support outputs. AI and deep learning (DL) find obvious applications in fields like ophthalmology wherein huge amount of image-based data need to be analyzed; however, the outcomes related to image recognition are reasonably well-defined. AI and DL have found important roles in ophthalmology in early screening and detection of conditions such as diabetic retinopathy (DR), age-related macular degeneration (ARMD), retinopathy of prematurity (ROP), glaucoma, and other ocular disorders, being successful inroads as far as early screening and diagnosis are concerned and appear promising with advantages of high-screening accuracy, consistency, and scalability. AI algorithms need equally skilled manpower, trained optometrists/ophthalmologists (annotators) to provide accurate ground truth for training the images. The basis of diagnoses made by AI algorithms is mechanical, and some amount of human intervention is necessary for further interpretations. This review was conducted after tracing the history of AI in ophthalmology across multiple research databases and aims to summarise the journey of AI in ophthalmology so far, making a close observation of most of the crucial studies conducted. This article further aims to highlight the potential impact of AI in ophthalmology, the pitfalls, and how to optimally use it to the maximum benefits of the ophthalmologists, the healthcare systems and the patients, alike.

Print this article     Email this article
 Next article
 Previous article
 Table of Contents

 Similar in PUBMED
   Search Pubmed for
   Search in Google Scholar for
 Related articles
 Citation Manager
 Access Statistics
 Reader Comments
 Email Alert *
 Add to My List *
 * Requires registration (Free)

 Article Access Statistics
    PDF Downloaded102    
    Comments [Add]    

Recommend this journal