Artificial intelligence in individualized retinal disease management
Author:
Corresponding Author:

Ke-Ran Li. The Affiliated Eye Hospital of Nanjing Medical University, Nanjing 210029, Jiangsu Province, China. kathykeran860327@126.com

Affiliation:

Clc Number:

Fund Project:

Supported by the National Natural Science Foundation of China (No.82171080); Nanjing Health Science and Technology Development Special Fund (No.YKK23264).

  • Article
  • |
  • Figures
  • |
  • Metrics
  • |
  • Reference
  • |
  • Related
  • |
  • Cited by
  • |
  • Materials
  • |
  • Comments
    Abstract:

    Owing to the rapid development of modern computer technologies, artificial intelligence (AI) has emerged as an essential instrument for intelligent analysis across a range of fields. AI has been proven to be highly effective in ophthalmology, where it is frequently used for identifying, diagnosing, and typing retinal diseases. An increasing number of researchers have begun to comprehensively map patients’ retinal diseases using AI, which has made individualized clinical prediction and treatment possible. These include prognostic improvement, risk prediction, progression assessment, and interventional therapies for retinal diseases. Researchers have used a range of input data methods to increase the accuracy and dependability of the results, including the use of tabular, textual, or image-based input data. They also combined the analyses of multiple types of input data. To give ophthalmologists access to precise, individualized, and high-quality treatment strategies that will further optimize treatment outcomes, this review summarizes the latest findings in AI research related to the prediction and guidance of clinical diagnosis and treatment of retinal diseases.

    Reference
    Related
    Cited by
Get Citation

Zi-Ran Zhang, Jia-Jun Li, Ke-Ran Li. Artificial intelligence in individualized retinal disease management. Int J Ophthalmol, 2024,17(8):1519-1530

Copy
Share
Article Metrics
  • Abstract:
  • PDF:
  • HTML:
  • Cited by:
Publication History
  • Received:January 04,2024
  • Revised:March 06,2024
  • Adopted:
  • Online: July 23,2024
  • Published: