What is Artificial Intelligence? Artificial intelligence, described simply, is the ability of a computer to mimic the intellectual intelligence unique to humans. This type of intelligence includes qualities such as the ability to link events to specific causes, make generalizations, and learn from experience. 1 As a general public notion, the term is used to describe devices that can provide a reason for a certain phenomenon, develop strategies, make judgments about situations, and have the ability to learn. However, there are ongoing controversies regarding the level and reliability of this intelligence. 2 Many different theories on how to evaluate machine intelligence have been proposed. The most famous of these is the Turing test, which was put forward in 1950 by Alan Turing, an English mathematician, computer scientist, and cryptologist. Artificial intelligence is advancing rapidly and making its way into all areas of our lives. This review discusses developments and potential practices regarding the use of artificial intelligence in the field of ophthalmology, and the related topic of medical ethics. Various artificial intelligence applications related to the diagnosis of eye diseases were researched in books, journals, search engines, print and social media. Resources were cross-checked to verify the information. Artificial intelligence algorithms, some of which were approved by the US Food and Drug Administration, have been adopted in the field of ophthalmology, especially in diagnostic studies. Studies are being conducted that prove that artificial intelligence algorithms can be used in the field of ophthalmology, especially in diabetic retinopathy, age-related macular degeneration, and retinopathy of prematurity. Some of these algorithms have come to the approval stage. The current point in artificial intelligence studies shows that this technology has advanced considerably and shows promise for future work. It is believed that artificial intelligence applications will be effective in identifying patients with preventable vision loss and directing them to physicians, especially in developing countries where there are fewer trained professionals and physicians are difficult to reach. When we consider the possibility that some future artificial intelligence systems may be candidates for moral/ethical status, certain ethical issues arise. Questions about moral/ethical status are important in some areas of applied ethics. Although it is accepted that current intelligence systems do not have moral/ethical status, it has yet to be determined what the exact the characteristics that confer moral/ethical status are or will be.

No author has a financial or proprietary interest in any material or method mentioned.

In patients with recently diagnosed PCOS, tear volume and osmolarity are not affected but, conjunctival morphology may be affected, though on a limited scale.

Introduction. Experimental animal models of acute uveitis, an inflammatory eye disease, can be established via endotoxin-induced inflammation. Propolis, a natural substance collected by honeybees from buds and tree exudates, has antioxidant, antibacterial, antiviral, and anti-inflammatory effects. We investigated the effects of propolis, obtained from the Sakarya province of Turkey, on endotoxin-induced uveitis using immunohistochemical, ultrastructural, and biochemical approaches. Material and methods. Male Wistar albino rats (n = 6/group) received intraperitoneal (ip) lipopolysaccharide (LPS) endotoxin (150 µg/kg) followed by aqueous extract of propolis (50 mg/kg ip) or vehicle; two additional groups received either saline (control) or propolis only. After 24 h, aqueous humor (AH) was collected from both eyes of each animal for analysis of tumor necrosis factor-a (TNF-a) and hypoxia-inducible factor-1a (HIF-1a). Right eyeballs were paraffin-embedded for immunohistochemical staining of nuclear factor kB (NF-kB)/p65 and left eyeballs were araldite-embedded for ultrastructural analysis. Results. Treatment of LPS-induced uveitis with propolis significantly reduced ciliary body NF-kB/p65 immunoreactivity and AH levels of HIF-1a and TNF-a. Ultrastructural analysis showed fewer vacuoles and reduced mitochondrial degeneration in the retinal pigment epithelium, as compared to the uveitis group. The intercellular spaces of the inner nuclear layer and outer limiting membrane were comparable with those of the control group; no polymorphonuclear cells or stasis was observed in intravascular or extravascular spaces. Conclusions. This is the first report demonstrating an anti-inflammatory effect of Turkish propolis in a rat model of LPS-induced acute uveitis, suggesting a therapeutic potential of propolis for the treatment of inflammatory ophthalmic diseases.

Summary Background We undertook a Grand Challenges in Global Eye Health prioritisation exercise to identify the key issues that must be addressed to improve eye health in the context of an ageing population, to eliminate persistent inequities in health-care access, and to mitigate widespread resource limitations. Methods Drawing on methods used in previous Grand Challenges studies, we used a multi-step recruitment strategy to assemble a diverse panel of individuals from a range of disciplines relevant to global eye health from all regions globally to participate in a three-round, online, Delphi-like, prioritisation process to nominate and rank challenges in global eye health. Through this process, we developed both global and regional priority lists. Findings Between Sept 1 and Dec 12, 2019, 470 individuals complete round 1 of the process, of whom 336 completed all three rounds (round 2 between Feb 26 and March 18, 2020, and round 3 between April 2 and April 25, 2020) 156 (46%) of 336 were women, 180 (54%) were men. The proportion of participants who worked in each region ranged from 104 (31%) in sub-Saharan Africa to 21 (6%) in central Europe, eastern Europe, and in central Asia. Of 85 unique challenges identified after round 1, 16 challenges were prioritised at the global level; six focused on detection and treatment of conditions (cataract, refractive error, glaucoma, diabetic retinopathy, services for children and screening for early detection), two focused on addressing shortages in human resource capacity, five on other health service and policy factors (including strengthening policies, integration, health information systems, and budget allocation), and three on improving access to care and promoting equity. Interpretation This list of Grand Challenges serves as a starting point for immediate action by funders to guide investment in research and innovation in eye health. It challenges researchers, clinicians, and policy makers to build collaborations to address specific challenges. Funding The Queen Elizabeth Diamond Jubilee Trust, Moorfields Eye Charity, National Institute for Health Research Moorfields Biomedical Research Centre, Wellcome Trust, Sightsavers, The Fred Hollows Foundation, The Seva Foundation, British Council for the Prevention of Blindness, and Christian Blind Mission. Translations For the French, Spanish, Chinese, Portuguese, Arabic and Persian translations of the abstract see Supplementary Materials section.