Applications of Artificial Intelligence in Ophthalmology: Glaucoma, Cornea, and Oculoplastics.

Autor: Labib KM; Department of Ophthalmology, University of South Florida Morsani College of Medicine, Tampa, USA., Ghumman H; Department of Ophthalmology, University of South Florida Morsani College of Medicine, Tampa, USA., Jain S; Department of Ophthalmology, University of South Florida Morsani College of Medicine, Tampa, USA., Jarstad JS; Department of Ophthalmology, University of South Florida Morsani College of Medicine, Tampa, USA.
Jazyk: angličtina
Zdroj: Cureus [Cureus] 2024 Nov 12; Vol. 16 (11), pp. e73522. Date of Electronic Publication: 2024 Nov 12 (Print Publication: 2024).
DOI: 10.7759/cureus.73522
Abstrakt: Artificial intelligence (AI) is transforming ophthalmology by leveraging machine learning (ML) and deep learning (DL) techniques, particularly artificial neural networks (ANN) and convolutional neural networks (CNN) to mimic human brain functions and enhance accuracy through data exposure. These AI systems are particularly effective in analyzing ophthalmic images for early disease detection, improving diagnostic precision, streamlining clinical workflows, and ultimately enhancing patient outcomes. This study aims to explore the specific applications and impact of AI in the fields of glaucoma, corneal diseases, and oculoplastics. This study reviews current AI technologies in ophthalmology, examining the implementation of ML and DL techniques. It evaluates AI's role in early disease detection, diagnostic accuracy, clinical workflow enhancement, and patient outcomes. AI has significantly advanced the early detection and management of various ocular conditions. In glaucoma, AI systems provide standardized, rapid identification of disease characteristics, reducing intra- and interobserver bias and workload. For corneal diseases, AI tools enhance diagnostic methods for conditions such as keratitis and keratoconus, improving early detection and treatment planning. In oculoplastics, AI assists in the diagnosis and monitoring of eyelid and orbital diseases, facilitating precise surgical planning and postoperative management. The integration of AI in ophthalmology has revolutionized eye care by enhancing diagnostic precision, streamlining clinical workflows, and improving patient outcomes. As AI technologies continue to evolve, their applications in ophthalmology are expected to expand, offering innovative solutions for the diagnosis, monitoring, treatment, and surgical outcomes of various eye conditions.
Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.
(Copyright © 2024, Labib et al.)
Databáze: MEDLINE