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Artificial intelligence: the unstoppable revolution in ophthalmology.
Benet, David; Pellicer-Valero, Oscar J.
  • Benet D; Independent Researcher, Spain. Electronic address: davidbenetferrus@gmail.com.
  • Pellicer-Valero OJ; Intelligent Data Analysis Laboratory, Department of Electronic Engineering, ETSE (Engineering School), Universitat de València (UV), Valencia, Spain.
Surv Ophthalmol ; 67(1): 252-270, 2022.
Article in English | MEDLINE | ID: covidwho-1573843
ABSTRACT
Artificial intelligence (AI) is an unstoppable force that is starting to permeate all aspects of our society as part of the revolution being brought into our lives (and into medicine) by the digital era, and accelerated by the current COVID-19 pandemic. As the population ages and developing countries move forward, AI-based systems may be a key asset in streamlining the screening, staging, and treatment planning of sight-threatening eye conditions, offloading the most tedious tasks from the experts, allowing for a greater population coverage, and bringing the best possible care to every patient. This paper presents a review of the state of the art of AI in the field of ophthalmology, focusing on the strengths and weaknesses of current systems, and defining the vision that will enable us to advance scientifically in this digital era. It starts with a thorough yet accessible introduction to the algorithms underlying all modern AI applications. Then, a critical review of the main AI applications in ophthalmology is presented, including diabetic retinopathy, age-related macular degeneration, retinopathy of prematurity, glaucoma, and other AI-related topics such as image enhancement. The review finishes with a brief discussion on the opportunities and challenges that the future of this field might hold.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Ophthalmology / Glaucoma / COVID-19 Type of study: Reviews Limits: Humans / Infant, Newborn Language: English Journal: Surv Ophthalmol Year: 2022 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Ophthalmology / Glaucoma / COVID-19 Type of study: Reviews Limits: Humans / Infant, Newborn Language: English Journal: Surv Ophthalmol Year: 2022 Document Type: Article